职务/职称
国家健康医疗大数据研究院（深圳）院长
香港中文大学（深圳）医学院副院长
香港中文大学（深圳）医学院附属第二医院院长
教育背景
复旦大学医学院 社会医学与卫生事业管理博士
复旦大学医学院 儿科和临床流行病学硕士
复旦大学医学院 预防医学学士
研究领域
医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向
电子邮件
guangjunyu@cuhk.edu.cn
个人简介
于广军，博士、研究员，博士生导师。目前担任香港中文大学（深圳）医学院副院长、国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。2020年入选国家百千万人才工程计划，同年获得人社部有突出贡献专家。2014年批准享受国务院特殊津贴，2014年获得上海卫生系统优秀学科带头人，2015年获得上海市领军人才，2018年获得上海优秀学术带头人。2021年所带领的团队获得交大医学院协同创新团队，同年获得上海市政府儿童工作白玉兰奖。
个人介绍
于广军，博士、研究员，博士生导师。目前担任国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院副院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。于教授近十年来，专注于医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向的研究。2016年以来以第一作者和通讯作者发表论文79篇。主编著作有：《走进移动健康时代》、《医疗大数据》、《儿童医生说》和《高危儿管理》。作为副主编的著作有《法国现代卫生体系概论》、《现代医院管理实务》、《中国医院管理指南》。2011年获得上海科技进步一等奖(第3排名)、中国医院协会科技创新一等奖(第2排名)；2013年获得国家科技进步二等奖(第3排名)；2017年获得中国医院协会科技进步二等奖(第1排名)、上海科技进步三等奖(第1排名)。2020年获得上海医院协会科技创新一等奖。2021年获得中国医院协会科技创新三等奖。
代表性论文
1.Wu D, Cui W, Wang X, Huo Y, Yu G, Chen J. Improvement in outpatient services using the WeChat calling system in the Shanghai Children's Hospital. Pak J Med Sci. 2021 Jul-Aug; 37(4):993-1000
2.Zhao T, Genchev GZ, Wu S, Yu G, Lu H, Feng J. Pitt-Hopkins syndrome: phenotypic and genotypic description of four unrelated patients and structural analysis of corresponding missense mutations. Neurogenetics. 2021 Jul;22(3):161-169
3.Hu YB, Chen YT, Liu SJ, Jiang F, Wu MQ, Yan CH, Tan JG, Yu GJ, Hu Y, Yin Y, Qu JJ, Li SH, Tong SL. Increasing prevalence and influencing factors of childhood asthma: a cross-sectional study in Shanghai, China. World J Pediatr. 2021 Aug; 17(4):419-428
4.Cai X, Genchev GZ, He P, Lu H, Yu G. Demographics, in-hospital analysis, and prevalence of 33 rare diseases with effective treatment in Shanghai. Orphanet J Rare Dis. 2021 Jun 8;16(1):262
5.Song X, Feng J, Lan X, Tang X, Xu W, Shen J, Yu G, Jia J, Zhang H, Lu Q, Wu S. Generation and characterization of an iPSC line (SHCMDLi001-A) from a 12-year-old Chinese Han patient with TRAF7 syndrome and of an iPSC line (SHCMDLi002-A) from a control individual. Stem Cell Res. 2021 May;53:102377
6.Hu Y, Jiang F, Tan J, Liu S, Li S, Wu M, Yan C, Yu G, Hu Y, Yin Y, Tong S. Environmental Exposure and Childhood Atopic Dermatitis in Shanghai: A Season-Stratified Time-Series Analysis. Dermatology. 2021 Jun 3:1-8
7.Ji M, Genchev GZ, Huang H, Xu T, Lu H, Yu G. Evaluation Framework for Successful Artificial Intelligence-Enabled Clinical Decision Support Systems: Mixed Methods Study. J Med Internet Res. 2021 Jun 2;23(6):e25929
8.Wu D, Zhu J, Wang X, Shi H, Huo Y, Liu M, Sun F, Lan H, Guo C, Liu H, Li T, Jiang L, Hu X, Li T, Xu J, Yao G, Zhu G, Yu G, Chen J. Rapid BMI Increases and Persistent Obesity in Small-for-Gestational-Age Infants. Front Pediatr. 2021 May 4;9:625853
9.Hu Y, Chen Y, Liu S, Jiang F, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Qu J, Li S, Tong S. Breastfeeding duration modified the effects of neonatal and familial risk factors on childhood asthma and allergy: a population-based study. Respir Res. 2021 Feb 6;22(1):41
10.Wang Y, Gao X, Zhang X, Xiao F, Hu H, Li X, Dong F, Sun M, Xiao Y, Ge T, Li D, Yu G, Liu Z, Zhang T. Microbial and metabolic features associated with outcome of infliximab therapy in pediatric Crohn's disease. Gut Microbes. 2021 Jan-Dec; 13(1): 1-18
11.Zheng X, Shen L, Jiang L, Shen X, Xu Y, Yu G, Wang Y. Parent and Teacher Training Increases Medication Adherence for Primary School Children With Attention-Deficit/Hyperactivity Disorder. Front Pediatr. 2020 Nov 9;8:486353
12.Lan X, Xu W, Tang X, Ye H, Song X, Lin L, Ren X, Yu G, Zhang H, Wu S. Spectrum of RB1 Germline Mutations and Clinical Features in Unrelated Chinese Patients With Retinoblastoma. Front Genet. 2020 Mar 11;11:142
13.Cun D, Zhang K, Yu G. Cost Analysis of Operating a Human Milk Bank in China. J Hum Lact. 2020 May;36(2):264-272
14.Feng J, Lan X, Shen J, Song X, Tang X, Xu W, Ren X, Zhang H, Yu G, Wu S. A de novo MAPRE2 variant in a patient with congenital symmetric circumferential skin creases type 2. Mol Genet Genomic Med. 2020 Feb;8(2):e1096
15.Hu Y, Xu Z, Jiang F, Li S, Liu S, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Tong S. Relative impact of meteorological factors and air pollutants on childhood allergic diseases in Shanghai, China. Sci Total Environ. 2020 Mar 1;706:135975
16.Sun H, Guo Y, Lan X, Jia J, Cai X, Zhang G, Xie J, Liang Q, Li Y, Yu G. PhenoModifier: a genetic modifier database for elucidating the genetic basis of human phenotypic variation. Nucleic Acids Res. 2020 Jan 8;48(D1):D977-D982
17.Cai X, Yang H, Genchev GZ, Lu H, Yu G. Analysis of economic burden and its associated factors of twenty-three rare diseases in Shanghai. Orphanet J Rare Dis. 2019 Oct 22;14(1):233
18.Ji H, Hu Y, Zhang T, Wang Y, Shen L, Wang S, Chen M, Wei M, Yu G. Allergic Comorbidity of Asthma or Wheezing, Allergic Rhinitis, and Eczema: Result From 333 029 Allergic Children in Shanghai, China. Am J Rhinol Allergy. 2020 Mar;34(2):189-195
19.Tang C, Sun H, Xiong Y, Yang J, Vitale C, Ruan L, Ai A, Yu G, Ma J, Bates D. Medication Use for Childhood Pneumonia at a Children's Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms. JMIR Med Inform. 2019 Mar 22;7(1):e12577
20.Sun H, Yu G. New insights into the pathogenicity of non-synonymous variants through multi-level analysis. Sci Rep. 2019 Feb 7;9(1):1667
21.Tian Y, Zhang C, Yu G, Hu X, Pu Z, Ma L. Influencing factors of the neurodevelopment of high-risk infants. Gen Psychiatr. 2018 Dec 18;31(3):e100034
22.Li X, Gao X, Hu H, Xiao Y, Li D, Yu G, Yu D, Zhang T, Wang Y. Clinical Efficacy and Microbiome Changes Following Fecal Microbiota Transplantation in Children With Recurrent Clostridium Difficile Infection. Front Microbiol. 2018 Nov 2;9:2622
23.Shi H, Yang X, Wu D, Wang X, Li T, Liu H, Guo C, Wang J, Hu X, Yu G, Chen J. Insights into infancy weight gain patterns for term small-for-gestational-age babies. Nutr J. 2018 Oct 29;17(1):97
24.Li XW, Ni X, Qian SY, Wang Q, Jiang RM, Xu WB, Zhang YC, Yu GJ, Chen Q, Shang YX, Zhao CS, Yu H, Zhang T, Liu G, Deng HL, Gao J, Ran XG, Yang QZ, Xu BL, Huang XY, Wu XD, Bao YX, Chen YP, Chen ZH, Liu QQ, Lu GP, Liu CF, Wang RB, Zhang GL, Gu F, Xu HM, Li Y, Yang T. Chinese guidelines for the diagnosis and treatment of hand, foot and mouth disease (2018 edition). World J Pediatr. 2018 Oct;14(5):437-447
25.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
26.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
27.Wang Y, Gao X, Ghozlane A, Hu H, Li X, Xiao Y, Li D, Yu G, Zhang T. Characteristics of Faecal Microbiota in Paediatric Crohn's Disease and Their Dynamic Changes During Infliximab Therapy. J Crohns Colitis. 2018 Feb 28;12(3):337-346
28.Yu R, Wang Y, Xiao Y, Mo L, Liu A, Li D, Ge T, Yu G, Zhang T. Prevalence of malnutrition and risk of undernutrition in hospitalised children with liver disease. J Nutr Sci. 2017 Oct 30;6:e55
29.Ning Q, Li Y, Wang Z, Zhou S, Sun H, Yu G. The Evolution and Expression Pattern of Human Overlapping lncRNA and Protein-coding Gene Pairs. Sci Rep. 2017 Mar 27;7:42775
30.Wang J, Gu J, Wang Y, Lin K, Liu S, Lu H, Zhang T, Yu G. 16S rDNA Gene Sequencing Analysis in Functional Dyspepsia Treated With Fecal Microbiota Transplantation. J Pediatr Gastroenterol Nutr. 2017 Mar;64(3):e80-e82
31.Wang Y, Li X, Ge T, Xiao Y, Liao Y, Cui Y, Zhang Y, Ho W, Yu G, Zhang T. Probiotics for prevention and treatment of respiratory tract infections in children: A systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore). 2016 Aug;95(31):e4509
32.Gu J, Wang Y, Liu S, Zhang T, Yu G, Lu H. Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing. Neurocomputing. 2016;06(SI): 66-72
33.Carson MB, Gu J, Yu G, Lu H. Identification of cancer-related genes and motifs in the human gene regulatory network. IET Syst Biol. 2015 Aug;9(4):128-34
34.Gao Z, Gu Y, Lv Z, Yu G, Zhou J. Practical electronic information system and printed recording promote management accuracy in an early-stage small-scale non-automatic biobank. Biopreserv Biobank. 2015 Feb;13(1):61-6
35.Cui W, Zheng P, Yang J, Zhao R, Gao J, Yu G. Integrating clinical and biological information in a shanghai biobank: an introduction to the sample repository and information sharing platform project. Biopreserv Biobank. 2015 Feb;13(1):37-42
36.Cao J, Li M, Wang Y, Yu G, Yan C. Environmental lead exposure among preschool children in Shanghai, China: blood lead levels and risk factors. PLoS One. 2014 Dec 1;9(12):e113297
37.Zhu Q, Yu G, Yu H, Lu Q, Gu X, Dong Z, Zhang X. A randomized control trial on interruption of HBV transmission in uterus. Chin Med J (Engl). 2003 May;116(5):685-7
职务/职称
国家健康医疗大数据研究院（深圳）院长
香港中文大学（深圳）医学院副院长
香港中文大学（深圳）医学院附属第二医院院长
教育背景
复旦大学医学院 社会医学与卫生事业管理博士
复旦大学医学院 儿科和临床流行病学硕士
复旦大学医学院 预防医学学士
研究领域
医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向
电子邮件
guangjunyu@cuhk.edu.cn
个人简介
于广军，博士、研究员，博士生导师。目前担任香港中文大学（深圳）医学院副院长、国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。2020年入选国家百千万人才工程计划，同年获得人社部有突出贡献专家。2014年批准享受国务院特殊津贴，2014年获得上海卫生系统优秀学科带头人，2015年获得上海市领军人才，2018年获得上海优秀学术带头人。2021年所带领的团队获得交大医学院协同创新团队，同年获得上海市政府儿童工作白玉兰奖。
个人介绍
于广军，博士、研究员，博士生导师。目前担任国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院副院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。于教授近十年来，专注于医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向的研究。2016年以来以第一作者和通讯作者发表论文79篇。主编著作有：《走进移动健康时代》、《医疗大数据》、《儿童医生说》和《高危儿管理》。作为副主编的著作有《法国现代卫生体系概论》、《现代医院管理实务》、《中国医院管理指南》。2011年获得上海科技进步一等奖(第3排名)、中国医院协会科技创新一等奖(第2排名)；2013年获得国家科技进步二等奖(第3排名)；2017年获得中国医院协会科技进步二等奖(第1排名)、上海科技进步三等奖(第1排名)。2020年获得上海医院协会科技创新一等奖。2021年获得中国医院协会科技创新三等奖。
代表性论文
1.Wu D, Cui W, Wang X, Huo Y, Yu G, Chen J. Improvement in outpatient services using the WeChat calling system in the Shanghai Children's Hospital. Pak J Med Sci. 2021 Jul-Aug; 37(4):993-1000
2.Zhao T, Genchev GZ, Wu S, Yu G, Lu H, Feng J. Pitt-Hopkins syndrome: phenotypic and genotypic description of four unrelated patients and structural analysis of corresponding missense mutations. Neurogenetics. 2021 Jul;22(3):161-169
3.Hu YB, Chen YT, Liu SJ, Jiang F, Wu MQ, Yan CH, Tan JG, Yu GJ, Hu Y, Yin Y, Qu JJ, Li SH, Tong SL. Increasing prevalence and influencing factors of childhood asthma: a cross-sectional study in Shanghai, China. World J Pediatr. 2021 Aug; 17(4):419-428
4.Cai X, Genchev GZ, He P, Lu H, Yu G. Demographics, in-hospital analysis, and prevalence of 33 rare diseases with effective treatment in Shanghai. Orphanet J Rare Dis. 2021 Jun 8;16(1):262
5.Song X, Feng J, Lan X, Tang X, Xu W, Shen J, Yu G, Jia J, Zhang H, Lu Q, Wu S. Generation and characterization of an iPSC line (SHCMDLi001-A) from a 12-year-old Chinese Han patient with TRAF7 syndrome and of an iPSC line (SHCMDLi002-A) from a control individual. Stem Cell Res. 2021 May;53:102377
6.Hu Y, Jiang F, Tan J, Liu S, Li S, Wu M, Yan C, Yu G, Hu Y, Yin Y, Tong S. Environmental Exposure and Childhood Atopic Dermatitis in Shanghai: A Season-Stratified Time-Series Analysis. Dermatology. 2021 Jun 3:1-8
7.Ji M, Genchev GZ, Huang H, Xu T, Lu H, Yu G. Evaluation Framework for Successful Artificial Intelligence-Enabled Clinical Decision Support Systems: Mixed Methods Study. J Med Internet Res. 2021 Jun 2;23(6):e25929
8.Wu D, Zhu J, Wang X, Shi H, Huo Y, Liu M, Sun F, Lan H, Guo C, Liu H, Li T, Jiang L, Hu X, Li T, Xu J, Yao G, Zhu G, Yu G, Chen J. Rapid BMI Increases and Persistent Obesity in Small-for-Gestational-Age Infants. Front Pediatr. 2021 May 4;9:625853
9.Hu Y, Chen Y, Liu S, Jiang F, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Qu J, Li S, Tong S. Breastfeeding duration modified the effects of neonatal and familial risk factors on childhood asthma and allergy: a population-based study. Respir Res. 2021 Feb 6;22(1):41
10.Wang Y, Gao X, Zhang X, Xiao F, Hu H, Li X, Dong F, Sun M, Xiao Y, Ge T, Li D, Yu G, Liu Z, Zhang T. Microbial and metabolic features associated with outcome of infliximab therapy in pediatric Crohn's disease. Gut Microbes. 2021 Jan-Dec; 13(1): 1-18
11.Zheng X, Shen L, Jiang L, Shen X, Xu Y, Yu G, Wang Y. Parent and Teacher Training Increases Medication Adherence for Primary School Children With Attention-Deficit/Hyperactivity Disorder. Front Pediatr. 2020 Nov 9;8:486353
12.Lan X, Xu W, Tang X, Ye H, Song X, Lin L, Ren X, Yu G, Zhang H, Wu S. Spectrum of RB1 Germline Mutations and Clinical Features in Unrelated Chinese Patients With Retinoblastoma. Front Genet. 2020 Mar 11;11:142
13.Cun D, Zhang K, Yu G. Cost Analysis of Operating a Human Milk Bank in China. J Hum Lact. 2020 May;36(2):264-272
14.Feng J, Lan X, Shen J, Song X, Tang X, Xu W, Ren X, Zhang H, Yu G, Wu S. A de novo MAPRE2 variant in a patient with congenital symmetric circumferential skin creases type 2. Mol Genet Genomic Med. 2020 Feb;8(2):e1096
15.Hu Y, Xu Z, Jiang F, Li S, Liu S, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Tong S. Relative impact of meteorological factors and air pollutants on childhood allergic diseases in Shanghai, China. Sci Total Environ. 2020 Mar 1;706:135975
16.Sun H, Guo Y, Lan X, Jia J, Cai X, Zhang G, Xie J, Liang Q, Li Y, Yu G. PhenoModifier: a genetic modifier database for elucidating the genetic basis of human phenotypic variation. Nucleic Acids Res. 2020 Jan 8;48(D1):D977-D982
17.Cai X, Yang H, Genchev GZ, Lu H, Yu G. Analysis of economic burden and its associated factors of twenty-three rare diseases in Shanghai. Orphanet J Rare Dis. 2019 Oct 22;14(1):233
18.Ji H, Hu Y, Zhang T, Wang Y, Shen L, Wang S, Chen M, Wei M, Yu G. Allergic Comorbidity of Asthma or Wheezing, Allergic Rhinitis, and Eczema: Result From 333 029 Allergic Children in Shanghai, China. Am J Rhinol Allergy. 2020 Mar;34(2):189-195
19.Tang C, Sun H, Xiong Y, Yang J, Vitale C, Ruan L, Ai A, Yu G, Ma J, Bates D. Medication Use for Childhood Pneumonia at a Children's Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms. JMIR Med Inform. 2019 Mar 22;7(1):e12577
20.Sun H, Yu G. New insights into the pathogenicity of non-synonymous variants through multi-level analysis. Sci Rep. 2019 Feb 7;9(1):1667
21.Tian Y, Zhang C, Yu G, Hu X, Pu Z, Ma L. Influencing factors of the neurodevelopment of high-risk infants. Gen Psychiatr. 2018 Dec 18;31(3):e100034
22.Li X, Gao X, Hu H, Xiao Y, Li D, Yu G, Yu D, Zhang T, Wang Y. Clinical Efficacy and Microbiome Changes Following Fecal Microbiota Transplantation in Children With Recurrent Clostridium Difficile Infection. Front Microbiol. 2018 Nov 2;9:2622
23.Shi H, Yang X, Wu D, Wang X, Li T, Liu H, Guo C, Wang J, Hu X, Yu G, Chen J. Insights into infancy weight gain patterns for term small-for-gestational-age babies. Nutr J. 2018 Oct 29;17(1):97
24.Li XW, Ni X, Qian SY, Wang Q, Jiang RM, Xu WB, Zhang YC, Yu GJ, Chen Q, Shang YX, Zhao CS, Yu H, Zhang T, Liu G, Deng HL, Gao J, Ran XG, Yang QZ, Xu BL, Huang XY, Wu XD, Bao YX, Chen YP, Chen ZH, Liu QQ, Lu GP, Liu CF, Wang RB, Zhang GL, Gu F, Xu HM, Li Y, Yang T. Chinese guidelines for the diagnosis and treatment of hand, foot and mouth disease (2018 edition). World J Pediatr. 2018 Oct;14(5):437-447
25.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
26.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
27.Wang Y, Gao X, Ghozlane A, Hu H, Li X, Xiao Y, Li D, Yu G, Zhang T. Characteristics of Faecal Microbiota in Paediatric Crohn's Disease and Their Dynamic Changes During Infliximab Therapy. J Crohns Colitis. 2018 Feb 28;12(3):337-346
28.Yu R, Wang Y, Xiao Y, Mo L, Liu A, Li D, Ge T, Yu G, Zhang T. Prevalence of malnutrition and risk of undernutrition in hospitalised children with liver disease. J Nutr Sci. 2017 Oct 30;6:e55
29.Ning Q, Li Y, Wang Z, Zhou S, Sun H, Yu G. The Evolution and Expression Pattern of Human Overlapping lncRNA and Protein-coding Gene Pairs. Sci Rep. 2017 Mar 27;7:42775
30.Wang J, Gu J, Wang Y, Lin K, Liu S, Lu H, Zhang T, Yu G. 16S rDNA Gene Sequencing Analysis in Functional Dyspepsia Treated With Fecal Microbiota Transplantation. J Pediatr Gastroenterol Nutr. 2017 Mar;64(3):e80-e82
31.Wang Y, Li X, Ge T, Xiao Y, Liao Y, Cui Y, Zhang Y, Ho W, Yu G, Zhang T. Probiotics for prevention and treatment of respiratory tract infections in children: A systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore). 2016 Aug;95(31):e4509
32.Gu J, Wang Y, Liu S, Zhang T, Yu G, Lu H. Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing. Neurocomputing. 2016;06(SI): 66-72
33.Carson MB, Gu J, Yu G, Lu H. Identification of cancer-related genes and motifs in the human gene regulatory network. IET Syst Biol. 2015 Aug;9(4):128-34
34.Gao Z, Gu Y, Lv Z, Yu G, Zhou J. Practical electronic information system and printed recording promote management accuracy in an early-stage small-scale non-automatic biobank. Biopreserv Biobank. 2015 Feb;13(1):61-6
35.Cui W, Zheng P, Yang J, Zhao R, Gao J, Yu G. Integrating clinical and biological information in a shanghai biobank: an introduction to the sample repository and information sharing platform project. Biopreserv Biobank. 2015 Feb;13(1):37-42
36.Cao J, Li M, Wang Y, Yu G, Yan C. Environmental lead exposure among preschool children in Shanghai, China: blood lead levels and risk factors. PLoS One. 2014 Dec 1;9(12):e113297
37.Zhu Q, Yu G, Yu H, Lu Q, Gu X, Dong Z, Zhang X. A randomized control trial on interruption of HBV transmission in uterus. Chin Med J (Engl). 2003 May;116(5):685-7
职务/职称
国家健康医疗大数据研究院（深圳）院长
香港中文大学（深圳）医学院副院长
香港中文大学（深圳）医学院附属第二医院院长
教育背景
复旦大学医学院 社会医学与卫生事业管理博士
复旦大学医学院 儿科和临床流行病学硕士
复旦大学医学院 预防医学学士
研究领域
医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向
电子邮件
guangjunyu@cuhk.edu.cn
个人简介
于广军，博士、研究员，博士生导师。目前担任香港中文大学（深圳）医学院副院长、国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。2020年入选国家百千万人才工程计划，同年获得人社部有突出贡献专家。2014年批准享受国务院特殊津贴，2014年获得上海卫生系统优秀学科带头人，2015年获得上海市领军人才，2018年获得上海优秀学术带头人。2021年所带领的团队获得交大医学院协同创新团队，同年获得上海市政府儿童工作白玉兰奖。
个人介绍
于广军，博士、研究员，博士生导师。目前担任国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院副院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。于教授近十年来，专注于医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向的研究。2016年以来以第一作者和通讯作者发表论文79篇。主编著作有：《走进移动健康时代》、《医疗大数据》、《儿童医生说》和《高危儿管理》。作为副主编的著作有《法国现代卫生体系概论》、《现代医院管理实务》、《中国医院管理指南》。2011年获得上海科技进步一等奖(第3排名)、中国医院协会科技创新一等奖(第2排名)；2013年获得国家科技进步二等奖(第3排名)；2017年获得中国医院协会科技进步二等奖(第1排名)、上海科技进步三等奖(第1排名)。2020年获得上海医院协会科技创新一等奖。2021年获得中国医院协会科技创新三等奖。
代表性论文
1.Wu D, Cui W, Wang X, Huo Y, Yu G, Chen J. Improvement in outpatient services using the WeChat calling system in the Shanghai Children's Hospital. Pak J Med Sci. 2021 Jul-Aug; 37(4):993-1000
2.Zhao T, Genchev GZ, Wu S, Yu G, Lu H, Feng J. Pitt-Hopkins syndrome: phenotypic and genotypic description of four unrelated patients and structural analysis of corresponding missense mutations. Neurogenetics. 2021 Jul;22(3):161-169
3.Hu YB, Chen YT, Liu SJ, Jiang F, Wu MQ, Yan CH, Tan JG, Yu GJ, Hu Y, Yin Y, Qu JJ, Li SH, Tong SL. Increasing prevalence and influencing factors of childhood asthma: a cross-sectional study in Shanghai, China. World J Pediatr. 2021 Aug; 17(4):419-428
4.Cai X, Genchev GZ, He P, Lu H, Yu G. Demographics, in-hospital analysis, and prevalence of 33 rare diseases with effective treatment in Shanghai. Orphanet J Rare Dis. 2021 Jun 8;16(1):262
5.Song X, Feng J, Lan X, Tang X, Xu W, Shen J, Yu G, Jia J, Zhang H, Lu Q, Wu S. Generation and characterization of an iPSC line (SHCMDLi001-A) from a 12-year-old Chinese Han patient with TRAF7 syndrome and of an iPSC line (SHCMDLi002-A) from a control individual. Stem Cell Res. 2021 May;53:102377
6.Hu Y, Jiang F, Tan J, Liu S, Li S, Wu M, Yan C, Yu G, Hu Y, Yin Y, Tong S. Environmental Exposure and Childhood Atopic Dermatitis in Shanghai: A Season-Stratified Time-Series Analysis. Dermatology. 2021 Jun 3:1-8
7.Ji M, Genchev GZ, Huang H, Xu T, Lu H, Yu G. Evaluation Framework for Successful Artificial Intelligence-Enabled Clinical Decision Support Systems: Mixed Methods Study. J Med Internet Res. 2021 Jun 2;23(6):e25929
8.Wu D, Zhu J, Wang X, Shi H, Huo Y, Liu M, Sun F, Lan H, Guo C, Liu H, Li T, Jiang L, Hu X, Li T, Xu J, Yao G, Zhu G, Yu G, Chen J. Rapid BMI Increases and Persistent Obesity in Small-for-Gestational-Age Infants. Front Pediatr. 2021 May 4;9:625853
9.Hu Y, Chen Y, Liu S, Jiang F, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Qu J, Li S, Tong S. Breastfeeding duration modified the effects of neonatal and familial risk factors on childhood asthma and allergy: a population-based study. Respir Res. 2021 Feb 6;22(1):41
10.Wang Y, Gao X, Zhang X, Xiao F, Hu H, Li X, Dong F, Sun M, Xiao Y, Ge T, Li D, Yu G, Liu Z, Zhang T. Microbial and metabolic features associated with outcome of infliximab therapy in pediatric Crohn's disease. Gut Microbes. 2021 Jan-Dec; 13(1): 1-18
11.Zheng X, Shen L, Jiang L, Shen X, Xu Y, Yu G, Wang Y. Parent and Teacher Training Increases Medication Adherence for Primary School Children With Attention-Deficit/Hyperactivity Disorder. Front Pediatr. 2020 Nov 9;8:486353
12.Lan X, Xu W, Tang X, Ye H, Song X, Lin L, Ren X, Yu G, Zhang H, Wu S. Spectrum of RB1 Germline Mutations and Clinical Features in Unrelated Chinese Patients With Retinoblastoma. Front Genet. 2020 Mar 11;11:142
13.Cun D, Zhang K, Yu G. Cost Analysis of Operating a Human Milk Bank in China. J Hum Lact. 2020 May;36(2):264-272
14.Feng J, Lan X, Shen J, Song X, Tang X, Xu W, Ren X, Zhang H, Yu G, Wu S. A de novo MAPRE2 variant in a patient with congenital symmetric circumferential skin creases type 2. Mol Genet Genomic Med. 2020 Feb;8(2):e1096
15.Hu Y, Xu Z, Jiang F, Li S, Liu S, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Tong S. Relative impact of meteorological factors and air pollutants on childhood allergic diseases in Shanghai, China. Sci Total Environ. 2020 Mar 1;706:135975
16.Sun H, Guo Y, Lan X, Jia J, Cai X, Zhang G, Xie J, Liang Q, Li Y, Yu G. PhenoModifier: a genetic modifier database for elucidating the genetic basis of human phenotypic variation. Nucleic Acids Res. 2020 Jan 8;48(D1):D977-D982
17.Cai X, Yang H, Genchev GZ, Lu H, Yu G. Analysis of economic burden and its associated factors of twenty-three rare diseases in Shanghai. Orphanet J Rare Dis. 2019 Oct 22;14(1):233
18.Ji H, Hu Y, Zhang T, Wang Y, Shen L, Wang S, Chen M, Wei M, Yu G. Allergic Comorbidity of Asthma or Wheezing, Allergic Rhinitis, and Eczema: Result From 333 029 Allergic Children in Shanghai, China. Am J Rhinol Allergy. 2020 Mar;34(2):189-195
19.Tang C, Sun H, Xiong Y, Yang J, Vitale C, Ruan L, Ai A, Yu G, Ma J, Bates D. Medication Use for Childhood Pneumonia at a Children's Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms. JMIR Med Inform. 2019 Mar 22;7(1):e12577
20.Sun H, Yu G. New insights into the pathogenicity of non-synonymous variants through multi-level analysis. Sci Rep. 2019 Feb 7;9(1):1667
21.Tian Y, Zhang C, Yu G, Hu X, Pu Z, Ma L. Influencing factors of the neurodevelopment of high-risk infants. Gen Psychiatr. 2018 Dec 18;31(3):e100034
22.Li X, Gao X, Hu H, Xiao Y, Li D, Yu G, Yu D, Zhang T, Wang Y. Clinical Efficacy and Microbiome Changes Following Fecal Microbiota Transplantation in Children With Recurrent Clostridium Difficile Infection. Front Microbiol. 2018 Nov 2;9:2622
23.Shi H, Yang X, Wu D, Wang X, Li T, Liu H, Guo C, Wang J, Hu X, Yu G, Chen J. Insights into infancy weight gain patterns for term small-for-gestational-age babies. Nutr J. 2018 Oct 29;17(1):97
24.Li XW, Ni X, Qian SY, Wang Q, Jiang RM, Xu WB, Zhang YC, Yu GJ, Chen Q, Shang YX, Zhao CS, Yu H, Zhang T, Liu G, Deng HL, Gao J, Ran XG, Yang QZ, Xu BL, Huang XY, Wu XD, Bao YX, Chen YP, Chen ZH, Liu QQ, Lu GP, Liu CF, Wang RB, Zhang GL, Gu F, Xu HM, Li Y, Yang T. Chinese guidelines for the diagnosis and treatment of hand, foot and mouth disease (2018 edition). World J Pediatr. 2018 Oct;14(5):437-447
25.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
26.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
27.Wang Y, Gao X, Ghozlane A, Hu H, Li X, Xiao Y, Li D, Yu G, Zhang T. Characteristics of Faecal Microbiota in Paediatric Crohn's Disease and Their Dynamic Changes During Infliximab Therapy. J Crohns Colitis. 2018 Feb 28;12(3):337-346
28.Yu R, Wang Y, Xiao Y, Mo L, Liu A, Li D, Ge T, Yu G, Zhang T. Prevalence of malnutrition and risk of undernutrition in hospitalised children with liver disease. J Nutr Sci. 2017 Oct 30;6:e55
29.Ning Q, Li Y, Wang Z, Zhou S, Sun H, Yu G. The Evolution and Expression Pattern of Human Overlapping lncRNA and Protein-coding Gene Pairs. Sci Rep. 2017 Mar 27;7:42775
30.Wang J, Gu J, Wang Y, Lin K, Liu S, Lu H, Zhang T, Yu G. 16S rDNA Gene Sequencing Analysis in Functional Dyspepsia Treated With Fecal Microbiota Transplantation. J Pediatr Gastroenterol Nutr. 2017 Mar;64(3):e80-e82
31.Wang Y, Li X, Ge T, Xiao Y, Liao Y, Cui Y, Zhang Y, Ho W, Yu G, Zhang T. Probiotics for prevention and treatment of respiratory tract infections in children: A systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore). 2016 Aug;95(31):e4509
32.Gu J, Wang Y, Liu S, Zhang T, Yu G, Lu H. Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing. Neurocomputing. 2016;06(SI): 66-72
33.Carson MB, Gu J, Yu G, Lu H. Identification of cancer-related genes and motifs in the human gene regulatory network. IET Syst Biol. 2015 Aug;9(4):128-34
34.Gao Z, Gu Y, Lv Z, Yu G, Zhou J. Practical electronic information system and printed recording promote management accuracy in an early-stage small-scale non-automatic biobank. Biopreserv Biobank. 2015 Feb;13(1):61-6
35.Cui W, Zheng P, Yang J, Zhao R, Gao J, Yu G. Integrating clinical and biological information in a shanghai biobank: an introduction to the sample repository and information sharing platform project. Biopreserv Biobank. 2015 Feb;13(1):37-42
36.Cao J, Li M, Wang Y, Yu G, Yan C. Environmental lead exposure among preschool children in Shanghai, China: blood lead levels and risk factors. PLoS One. 2014 Dec 1;9(12):e113297
37.Zhu Q, Yu G, Yu H, Lu Q, Gu X, Dong Z, Zhang X. A randomized control trial on interruption of HBV transmission in uterus. Chin Med J (Engl). 2003 May;116(5):685-7
职务/职称
国家健康医疗大数据研究院（深圳）院长
香港中文大学（深圳）医学院副院长
香港中文大学（深圳）医学院附属第二医院院长
教育背景
复旦大学医学院 社会医学与卫生事业管理博士
复旦大学医学院 儿科和临床流行病学硕士
复旦大学医学院 预防医学学士
研究领域
医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向
电子邮件
guangjunyu@cuhk.edu.cn
个人简介
于广军，博士、研究员，博士生导师。目前担任香港中文大学（深圳）医学院副院长、国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。2020年入选国家百千万人才工程计划，同年获得人社部有突出贡献专家。2014年批准享受国务院特殊津贴，2014年获得上海卫生系统优秀学科带头人，2015年获得上海市领军人才，2018年获得上海优秀学术带头人。2021年所带领的团队获得交大医学院协同创新团队，同年获得上海市政府儿童工作白玉兰奖。
个人介绍
于广军，博士、研究员，博士生导师。目前担任国家健康医疗大数据研究院（深圳）院长、香港中文大学（深圳）医学院副院长、香港中文大学（深圳）医学院附属第二医院院长、上海交通大学中国医院发展研究院医疗信息研究所所长、上海儿童精准医学大数据工程技术研究中心主任、上海交大医学院儿童感染免疫研究院院长、上海市儿童医院儿童早期发展基地负责人。于教授近十年来，专注于医疗大数据、互联网医疗和智慧医院、高危儿管理、多动症医教结合等方向的研究。2016年以来以第一作者和通讯作者发表论文79篇。主编著作有：《走进移动健康时代》、《医疗大数据》、《儿童医生说》和《高危儿管理》。作为副主编的著作有《法国现代卫生体系概论》、《现代医院管理实务》、《中国医院管理指南》。2011年获得上海科技进步一等奖(第3排名)、中国医院协会科技创新一等奖(第2排名)；2013年获得国家科技进步二等奖(第3排名)；2017年获得中国医院协会科技进步二等奖(第1排名)、上海科技进步三等奖(第1排名)。2020年获得上海医院协会科技创新一等奖。2021年获得中国医院协会科技创新三等奖。
代表性论文
1.Wu D, Cui W, Wang X, Huo Y, Yu G, Chen J. Improvement in outpatient services using the WeChat calling system in the Shanghai Children's Hospital. Pak J Med Sci. 2021 Jul-Aug; 37(4):993-1000
2.Zhao T, Genchev GZ, Wu S, Yu G, Lu H, Feng J. Pitt-Hopkins syndrome: phenotypic and genotypic description of four unrelated patients and structural analysis of corresponding missense mutations. Neurogenetics. 2021 Jul;22(3):161-169
3.Hu YB, Chen YT, Liu SJ, Jiang F, Wu MQ, Yan CH, Tan JG, Yu GJ, Hu Y, Yin Y, Qu JJ, Li SH, Tong SL. Increasing prevalence and influencing factors of childhood asthma: a cross-sectional study in Shanghai, China. World J Pediatr. 2021 Aug; 17(4):419-428
4.Cai X, Genchev GZ, He P, Lu H, Yu G. Demographics, in-hospital analysis, and prevalence of 33 rare diseases with effective treatment in Shanghai. Orphanet J Rare Dis. 2021 Jun 8;16(1):262
5.Song X, Feng J, Lan X, Tang X, Xu W, Shen J, Yu G, Jia J, Zhang H, Lu Q, Wu S. Generation and characterization of an iPSC line (SHCMDLi001-A) from a 12-year-old Chinese Han patient with TRAF7 syndrome and of an iPSC line (SHCMDLi002-A) from a control individual. Stem Cell Res. 2021 May;53:102377
6.Hu Y, Jiang F, Tan J, Liu S, Li S, Wu M, Yan C, Yu G, Hu Y, Yin Y, Tong S. Environmental Exposure and Childhood Atopic Dermatitis in Shanghai: A Season-Stratified Time-Series Analysis. Dermatology. 2021 Jun 3:1-8
7.Ji M, Genchev GZ, Huang H, Xu T, Lu H, Yu G. Evaluation Framework for Successful Artificial Intelligence-Enabled Clinical Decision Support Systems: Mixed Methods Study. J Med Internet Res. 2021 Jun 2;23(6):e25929
8.Wu D, Zhu J, Wang X, Shi H, Huo Y, Liu M, Sun F, Lan H, Guo C, Liu H, Li T, Jiang L, Hu X, Li T, Xu J, Yao G, Zhu G, Yu G, Chen J. Rapid BMI Increases and Persistent Obesity in Small-for-Gestational-Age Infants. Front Pediatr. 2021 May 4;9:625853
9.Hu Y, Chen Y, Liu S, Jiang F, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Qu J, Li S, Tong S. Breastfeeding duration modified the effects of neonatal and familial risk factors on childhood asthma and allergy: a population-based study. Respir Res. 2021 Feb 6;22(1):41
10.Wang Y, Gao X, Zhang X, Xiao F, Hu H, Li X, Dong F, Sun M, Xiao Y, Ge T, Li D, Yu G, Liu Z, Zhang T. Microbial and metabolic features associated with outcome of infliximab therapy in pediatric Crohn's disease. Gut Microbes. 2021 Jan-Dec; 13(1): 1-18
11.Zheng X, Shen L, Jiang L, Shen X, Xu Y, Yu G, Wang Y. Parent and Teacher Training Increases Medication Adherence for Primary School Children With Attention-Deficit/Hyperactivity Disorder. Front Pediatr. 2020 Nov 9;8:486353
12.Lan X, Xu W, Tang X, Ye H, Song X, Lin L, Ren X, Yu G, Zhang H, Wu S. Spectrum of RB1 Germline Mutations and Clinical Features in Unrelated Chinese Patients With Retinoblastoma. Front Genet. 2020 Mar 11;11:142
13.Cun D, Zhang K, Yu G. Cost Analysis of Operating a Human Milk Bank in China. J Hum Lact. 2020 May;36(2):264-272
14.Feng J, Lan X, Shen J, Song X, Tang X, Xu W, Ren X, Zhang H, Yu G, Wu S. A de novo MAPRE2 variant in a patient with congenital symmetric circumferential skin creases type 2. Mol Genet Genomic Med. 2020 Feb;8(2):e1096
15.Hu Y, Xu Z, Jiang F, Li S, Liu S, Wu M, Yan C, Tan J, Yu G, Hu Y, Yin Y, Tong S. Relative impact of meteorological factors and air pollutants on childhood allergic diseases in Shanghai, China. Sci Total Environ. 2020 Mar 1;706:135975
16.Sun H, Guo Y, Lan X, Jia J, Cai X, Zhang G, Xie J, Liang Q, Li Y, Yu G. PhenoModifier: a genetic modifier database for elucidating the genetic basis of human phenotypic variation. Nucleic Acids Res. 2020 Jan 8;48(D1):D977-D982
17.Cai X, Yang H, Genchev GZ, Lu H, Yu G. Analysis of economic burden and its associated factors of twenty-three rare diseases in Shanghai. Orphanet J Rare Dis. 2019 Oct 22;14(1):233
18.Ji H, Hu Y, Zhang T, Wang Y, Shen L, Wang S, Chen M, Wei M, Yu G. Allergic Comorbidity of Asthma or Wheezing, Allergic Rhinitis, and Eczema: Result From 333 029 Allergic Children in Shanghai, China. Am J Rhinol Allergy. 2020 Mar;34(2):189-195
19.Tang C, Sun H, Xiong Y, Yang J, Vitale C, Ruan L, Ai A, Yu G, Ma J, Bates D. Medication Use for Childhood Pneumonia at a Children's Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms. JMIR Med Inform. 2019 Mar 22;7(1):e12577
20.Sun H, Yu G. New insights into the pathogenicity of non-synonymous variants through multi-level analysis. Sci Rep. 2019 Feb 7;9(1):1667
21.Tian Y, Zhang C, Yu G, Hu X, Pu Z, Ma L. Influencing factors of the neurodevelopment of high-risk infants. Gen Psychiatr. 2018 Dec 18;31(3):e100034
22.Li X, Gao X, Hu H, Xiao Y, Li D, Yu G, Yu D, Zhang T, Wang Y. Clinical Efficacy and Microbiome Changes Following Fecal Microbiota Transplantation in Children With Recurrent Clostridium Difficile Infection. Front Microbiol. 2018 Nov 2;9:2622
23.Shi H, Yang X, Wu D, Wang X, Li T, Liu H, Guo C, Wang J, Hu X, Yu G, Chen J. Insights into infancy weight gain patterns for term small-for-gestational-age babies. Nutr J. 2018 Oct 29;17(1):97
24.Li XW, Ni X, Qian SY, Wang Q, Jiang RM, Xu WB, Zhang YC, Yu GJ, Chen Q, Shang YX, Zhao CS, Yu H, Zhang T, Liu G, Deng HL, Gao J, Ran XG, Yang QZ, Xu BL, Huang XY, Wu XD, Bao YX, Chen YP, Chen ZH, Liu QQ, Lu GP, Liu CF, Wang RB, Zhang GL, Gu F, Xu HM, Li Y, Yang T. Chinese guidelines for the diagnosis and treatment of hand, foot and mouth disease (2018 edition). World J Pediatr. 2018 Oct;14(5):437-447
25.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
26.Wang X, Zhu J, Guo C, Shi H, Wu D, Sun F, Shen L, Ge P, Wang J, Hu X, Chen J, Yu G. Growth of infants and young children born small for gestational age: growth restriction accompanied by overweight. J Int Med Res. 2018 Sep;46(9):3765-3777
27.Wang Y, Gao X, Ghozlane A, Hu H, Li X, Xiao Y, Li D, Yu G, Zhang T. Characteristics of Faecal Microbiota in Paediatric Crohn's Disease and Their Dynamic Changes During Infliximab Therapy. J Crohns Colitis. 2018 Feb 28;12(3):337-346
28.Yu R, Wang Y, Xiao Y, Mo L, Liu A, Li D, Ge T, Yu G, Zhang T. Prevalence of malnutrition and risk of undernutrition in hospitalised children with liver disease. J Nutr Sci. 2017 Oct 30;6:e55
29.Ning Q, Li Y, Wang Z, Zhou S, Sun H, Yu G. The Evolution and Expression Pattern of Human Overlapping lncRNA and Protein-coding Gene Pairs. Sci Rep. 2017 Mar 27;7:42775
30.Wang J, Gu J, Wang Y, Lin K, Liu S, Lu H, Zhang T, Yu G. 16S rDNA Gene Sequencing Analysis in Functional Dyspepsia Treated With Fecal Microbiota Transplantation. J Pediatr Gastroenterol Nutr. 2017 Mar;64(3):e80-e82
31.Wang Y, Li X, Ge T, Xiao Y, Liao Y, Cui Y, Zhang Y, Ho W, Yu G, Zhang T. Probiotics for prevention and treatment of respiratory tract infections in children: A systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore). 2016 Aug;95(31):e4509
32.Gu J, Wang Y, Liu S, Zhang T, Yu G, Lu H. Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing. Neurocomputing. 2016;06(SI): 66-72
33.Carson MB, Gu J, Yu G, Lu H. Identification of cancer-related genes and motifs in the human gene regulatory network. IET Syst Biol. 2015 Aug;9(4):128-34
34.Gao Z, Gu Y, Lv Z, Yu G, Zhou J. Practical electronic information system and printed recording promote management accuracy in an early-stage small-scale non-automatic biobank. Biopreserv Biobank. 2015 Feb;13(1):61-6
35.Cui W, Zheng P, Yang J, Zhao R, Gao J, Yu G. Integrating clinical and biological information in a shanghai biobank: an introduction to the sample repository and information sharing platform project. Biopreserv Biobank. 2015 Feb;13(1):37-42
36.Cao J, Li M, Wang Y, Yu G, Yan C. Environmental lead exposure among preschool children in Shanghai, China: blood lead levels and risk factors. PLoS One. 2014 Dec 1;9(12):e113297
37.Zhu Q, Yu G, Yu H, Lu Q, Gu X, Dong Z, Zhang X. A randomized control trial on interruption of HBV transmission in uterus. Chin Med J (Engl). 2003 May;116(5):685-7
POSITION/TITLE
Lab Director of Medical Big Data Laboratory
EDUCATION BACKGROUND
Ph.D. Computing Science, University of Alberta, 2006
M.S. Computing Science, University of Alberta, 2001
B.S. Information System, Renmin University, 1994
RESEARCH FIELD
Meta-analysis, Data Mining, Large-scale Genomic Data Analysis, High Performance Computing, Evidence-based Medicine
wanxiang@sribd.cn
BIOGRAPHY
Professor Wan received his BA in Information System from Renmin University and his MA and Ph.D. in Computing Science from University of Alberta. Professor Wan was a research assistant professor at Hong Kong Baptist University from 2012 to 2018. And he is now working concurrently as a research scientist at Shenzhen Research Institute of Big Data since 2018.
Professor Wan has been mainly working on meta-analysis and statistical learning, particularly in the field of large-scale genomic data analysis. He has published more than 40 papers in many top-tier journals, including Nature Genetics, American Journal of Human Genetics, BMC Genetics, Bioinformatics, BMC Bioinformatics, Neuro-informatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics, etc. Professor Wan is currently the director of Medical Big Data Lab. The main research goal of this lab is to integrate electronic medical records, medical imaging, health check reports and multi-omics data to help the pre-diagnosis and the personalized treatment.
ACADEMIC PUBLICATIONS
1. Can Yang, Xiang Wan*, Xinyi Lin, Mengjie Chen, Xiang Zhou, Jin Liu. CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information, Bioinformatics 35(10) 1644-1652, 2019. (co-first author)
2. Jingsi Ming, Mingwei Dai, Mingxuan Cai, Xiang Wan, Jin Liu, Can Yang. LSMM: a statistical approach to integrating functional annotations with genome-wide association studies. Bioinformatics, 2019, 34 (16), 2788-2796.
3. Mingwei Dai, Xiang Wan, Heng Peng, Yao Wang, Yue Liu, Jin Liu, Zongben Xu, Can Yang. Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy. Bioinformatics, 2019, Bioinformatics 35 (10), 1729-1736.
4. Lili Yue, Gaorong Li, Heng Lian, Xiang Wan. Regression adjustment for treatment effect with multicollinearity in high dimensions. Computational Statistics & Data Analysis, 2019, 134:17-35.
5. Guanying Wu, Xiang Wan*, Baohua Xu. A new estimation of protein-level false discovery rate. BMC Genomics, 2018, 2018 Aug 13;19 (Suppl 6):567. doi: 10.1186/s12864-018-4923-3. (co-first author)
6. Dehui Luo, Xiang Wan*, Jiming Liu, Tiejun Tong,Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range，Statistical methods in medical research， 2018， 27 (6), 1785-1805. (co-correspondence author)
7. Yan Zhou, Xiang Wan*, Baoxue Zhang, Tiejun Tong, Classifying next-generation sequencing data using a zero-inflated Poisson model, Bioinformatics，2018， 15;34(8):1329-1335. (co-correspondence author)
8. Jin Liu, Xiang Wan*, Chaolong Wang, Chao Yang, Xiaowen Zhou, Can Yang, LLR: A latent low-rank approach to colocalizing genetic risk variants in multiple GWAS,Bioinformatics, 2017, 33(24):3878-3886. (co-first author)
9. Mingwei Dai, Jingsi Ming, Mingxuan Cai, Jin Liu, Can Yang, Xiang Wan*, ZongbenXue, IGESS: A Statistical Approach to Integrating Individual-Level Genotype Data and Summary Statistics in Genome-Wide Association Studies, Bioinformatics,2017,33(18): 2882-2889. (co-correspondence author)
10. Bin Zhang, Xiang Wan*, Yuhao Dong, Dehui Luo, Jing Liu, Long Liang, Wenbo Chen, Xiaoning Luo, Xiaokai Mo, Lu Zhang, Wenhui Huang, Shufang Pei, Fusheng Ouyang, Baoliang Guo, Changhong Liang, Zhouyang Lian, Shuixing Zhang, Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children, Scientific Report, 2017 Jul 14;7(1):5368. (co-first author)
11. Yan Zhou, Baoxue Zhou, Tiejun Tong, Xiang Wan*. GD-RDA: A New Regularized Discriminant Analysis for High-Dimensional Data, Journal of Computational Biology, 2017,24 (11), 1099-1111. (correspondence author)
12. Kai Dong, Hongyu Zhao, Tiejun Tong, Xiang Wan*. NBLDA: Negative Binomial Linear Discriminant Analysis for RNA-Seq Data,BMC Bioinformatics,2016, 17(1):369. (co-correspondence author)
13. Ruixing Ming, Jiming Liu, William K.W. Cheung, Xiang Wan*. Stochastic Modeling of Infectious Diseases for Heterogeneous Populations. BMC Infectious Disease, 2016,5(1):107. (correspondence author)
14. Jin Liu, Xiang Wan, Shuangge Ma, Can Yang. EPS: An empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genes, Bioinformatics, 2016, 32(12):1856-64
15. Ben Teng, Can Yang, Jiming Liu, Zhipeng Cai, Xiang Wan*. Exploring the genetic patterns of complex diseases via the integrative genome-wide approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015, 13(3): 557-664. (correspondence author)
16. Xiang Wan, Wenqian Wang, Jiming Liu, Tiejun Tong. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC medical research methodology, 14 (1), 135, 2014.
17. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Learning to improve medical decision making from imbalanced data without a priori cost. BMC medical informatics and decision making, 14 (1), 1, 2014.
18. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Inferring Epidemic Network Topology from Surveillance Data. Plos ONE, 9(6):e100661, 2014.
19. Xiaowei Zhou, Jiming Liu, Xiang Wan*, Weichuan Yu. Piecewise-constant and low-rank approximation for identification of recurrent copy number variations. Bioinformatics, 30(14):1943-1949, 2014. (correspondence author)
20. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 230-235, 2013.
21. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies. IEEE/ACM Transactions on Computational Biology and Bioinformatics, (1): 207-212, 2013.
22. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. The complete compositional epistasis detection in genome-wide association studies, BMC Genetics, 14(1):7, 2013.
23. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 207-212, 2013.
24. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization, IEEE/ACM Transactions on Computational Biology and Bioinformatics , 10(1), 207-212, 2013.
25. Xiang Wan, Can Yang, Weichuan Yu. Comments on 'An empirical comparison of several recent epistatic interaction detection methods', Bioinformatics, 28(1):145-146, 2012.
26. Geng Cui, Man Leung Wong, Xiang Wan. Cost-Sensitive Learning via Priority Sampling to Improve the Return on Marketing and CRM. Journal of Management Information System, 29(1):341-374, 2012.
27. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. A new two-locus disease association pattern identified in genome-wide association studies, BMC Bioinformatics, 12:156, 2011. (co-first author)
28. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. The choice of null distributions for detecting gene-gene interactions in genome-wide association studies, BMC Bioinformatics, 12(Suppl 1):S26, 2011. (co-first author)
29. Lingxing Yung, Can Yang, Xiang Wan, Weichuan Yu. GBOOST: A GPU-Based Tool for Detecting Gene-Gene Interactions in Genome-Wide Case Control Studies, Bioinformatics, 28(1):145-146, 2011
30. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Xiaodan Fan, Nelson L.S. Tang, Weichuan Yu. BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies, American Journal of Human Genetics, 87(3), 325-340, 2010.
31. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Detecting two-locus associations allowing for interactions in genome-wide association studies, Bioinformatics, 26(20): 2517-2525, 2010.
32. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Predictive rule inference for epistatic interaction detection in genome-wide association study, Bioinformatics, 26(1):30-37, 2010.
33. Can Yang, Xiang Wan, Qiang Yang, Hong Xue, Weichuan Yu. Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group lasso, BMC Bioinformatics, 11(Suppl 1):S18, 2010.
34. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome-wide association study, BMC Bioinformatics, 10:13, 2009.
35. Kimberly L Stark, Bin Xu, Anindya Bagchi, Wen-Sung Lai, Hui Liu, Ruby Hsu, Xiang Wan, Paul Pavlidis, Alea A Mills, Maria Karayiorgou1 & Joseph A Gogos Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model, Nature Genetics, 40, 751 – 760, 2008.
36. Can Yang, Zengyou He, Xiang Wan, Weichuan Yu, Qiang Yang, Hong Xue, SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies, Bioinformatics, doi:10.1093, 2008.
37. Xiang Wan, Paul Pavlidis. Sharing and reusing gene expression profiling data in neuroscience, Neuroinformatics, 5(3), 161-175, 2007.
38. Xiang Wan, Guohui Lin. CISA: Combined NMR Resonance Connectivity Information Determination and Sequential Assignment, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(3), 336-348, 2007.
39. Xiang Wan, Guohui Lin. A Graph-Based Automated NMR Backbone Resonance Sequential Assignment, Journal of Bioinformatics and Computational Biology, 5(2), 313-333, 2007.
40. Guohui Lin, Xiang Wan, Theodos Tegos, Yingshu Li. Statistical Evaluation of NMR Backbone Resonance Assignment, International Journal of Bioinformatics Research and Applications, 2(2), 147-160, 2006.
41. Xiang Wan, Theodos Tegos, Guohui Lin. Histogram-based Scoring Schemes for Protein NMR Resonance Assignment, Journal of Bioinformatics and Computational Biology, 2.
POSITION/TITLE
Lab Director of Medical Big Data Laboratory
EDUCATION BACKGROUND
Ph.D. Computing Science, University of Alberta, 2006
M.S. Computing Science, University of Alberta, 2001
B.S. Information System, Renmin University, 1994
RESEARCH FIELD
Meta-analysis, Data Mining, Large-scale Genomic Data Analysis, High Performance Computing, Evidence-based Medicine
wanxiang@sribd.cn
BIOGRAPHY
Professor Wan received his BA in Information System from Renmin University and his MA and Ph.D. in Computing Science from University of Alberta. Professor Wan was a research assistant professor at Hong Kong Baptist University from 2012 to 2018. And he is now working concurrently as a research scientist at Shenzhen Research Institute of Big Data since 2018.
Professor Wan has been mainly working on meta-analysis and statistical learning, particularly in the field of large-scale genomic data analysis. He has published more than 40 papers in many top-tier journals, including Nature Genetics, American Journal of Human Genetics, BMC Genetics, Bioinformatics, BMC Bioinformatics, Neuro-informatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics, etc. Professor Wan is currently the director of Medical Big Data Lab. The main research goal of this lab is to integrate electronic medical records, medical imaging, health check reports and multi-omics data to help the pre-diagnosis and the personalized treatment.
ACADEMIC PUBLICATIONS
1. Can Yang, Xiang Wan*, Xinyi Lin, Mengjie Chen, Xiang Zhou, Jin Liu. CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information, Bioinformatics 35(10) 1644-1652, 2019. (co-first author)
2. Jingsi Ming, Mingwei Dai, Mingxuan Cai, Xiang Wan, Jin Liu, Can Yang. LSMM: a statistical approach to integrating functional annotations with genome-wide association studies. Bioinformatics, 2019, 34 (16), 2788-2796.
3. Mingwei Dai, Xiang Wan, Heng Peng, Yao Wang, Yue Liu, Jin Liu, Zongben Xu, Can Yang. Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy. Bioinformatics, 2019, Bioinformatics 35 (10), 1729-1736.
4. Lili Yue, Gaorong Li, Heng Lian, Xiang Wan. Regression adjustment for treatment effect with multicollinearity in high dimensions. Computational Statistics & Data Analysis, 2019, 134:17-35.
5. Guanying Wu, Xiang Wan*, Baohua Xu. A new estimation of protein-level false discovery rate. BMC Genomics, 2018, 2018 Aug 13;19 (Suppl 6):567. doi: 10.1186/s12864-018-4923-3. (co-first author)
6. Dehui Luo, Xiang Wan*, Jiming Liu, Tiejun Tong,Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range，Statistical methods in medical research， 2018， 27 (6), 1785-1805. (co-correspondence author)
7. Yan Zhou, Xiang Wan*, Baoxue Zhang, Tiejun Tong, Classifying next-generation sequencing data using a zero-inflated Poisson model, Bioinformatics，2018， 15;34(8):1329-1335. (co-correspondence author)
8. Jin Liu, Xiang Wan*, Chaolong Wang, Chao Yang, Xiaowen Zhou, Can Yang, LLR: A latent low-rank approach to colocalizing genetic risk variants in multiple GWAS,Bioinformatics, 2017, 33(24):3878-3886. (co-first author)
9. Mingwei Dai, Jingsi Ming, Mingxuan Cai, Jin Liu, Can Yang, Xiang Wan*, ZongbenXue, IGESS: A Statistical Approach to Integrating Individual-Level Genotype Data and Summary Statistics in Genome-Wide Association Studies, Bioinformatics,2017,33(18): 2882-2889. (co-correspondence author)
10. Bin Zhang, Xiang Wan*, Yuhao Dong, Dehui Luo, Jing Liu, Long Liang, Wenbo Chen, Xiaoning Luo, Xiaokai Mo, Lu Zhang, Wenhui Huang, Shufang Pei, Fusheng Ouyang, Baoliang Guo, Changhong Liang, Zhouyang Lian, Shuixing Zhang, Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children, Scientific Report, 2017 Jul 14;7(1):5368. (co-first author)
11. Yan Zhou, Baoxue Zhou, Tiejun Tong, Xiang Wan*. GD-RDA: A New Regularized Discriminant Analysis for High-Dimensional Data, Journal of Computational Biology, 2017,24 (11), 1099-1111. (correspondence author)
12. Kai Dong, Hongyu Zhao, Tiejun Tong, Xiang Wan*. NBLDA: Negative Binomial Linear Discriminant Analysis for RNA-Seq Data,BMC Bioinformatics,2016, 17(1):369. (co-correspondence author)
13. Ruixing Ming, Jiming Liu, William K.W. Cheung, Xiang Wan*. Stochastic Modeling of Infectious Diseases for Heterogeneous Populations. BMC Infectious Disease, 2016,5(1):107. (correspondence author)
14. Jin Liu, Xiang Wan, Shuangge Ma, Can Yang. EPS: An empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genes, Bioinformatics, 2016, 32(12):1856-64
15. Ben Teng, Can Yang, Jiming Liu, Zhipeng Cai, Xiang Wan*. Exploring the genetic patterns of complex diseases via the integrative genome-wide approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015, 13(3): 557-664. (correspondence author)
16. Xiang Wan, Wenqian Wang, Jiming Liu, Tiejun Tong. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC medical research methodology, 14 (1), 135, 2014.
17. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Learning to improve medical decision making from imbalanced data without a priori cost. BMC medical informatics and decision making, 14 (1), 1, 2014.
18. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Inferring Epidemic Network Topology from Surveillance Data. Plos ONE, 9(6):e100661, 2014.
19. Xiaowei Zhou, Jiming Liu, Xiang Wan*, Weichuan Yu. Piecewise-constant and low-rank approximation for identification of recurrent copy number variations. Bioinformatics, 30(14):1943-1949, 2014. (correspondence author)
20. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 230-235, 2013.
21. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies. IEEE/ACM Transactions on Computational Biology and Bioinformatics, (1): 207-212, 2013.
22. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. The complete compositional epistasis detection in genome-wide association studies, BMC Genetics, 14(1):7, 2013.
23. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 207-212, 2013.
24. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization, IEEE/ACM Transactions on Computational Biology and Bioinformatics , 10(1), 207-212, 2013.
25. Xiang Wan, Can Yang, Weichuan Yu. Comments on 'An empirical comparison of several recent epistatic interaction detection methods', Bioinformatics, 28(1):145-146, 2012.
26. Geng Cui, Man Leung Wong, Xiang Wan. Cost-Sensitive Learning via Priority Sampling to Improve the Return on Marketing and CRM. Journal of Management Information System, 29(1):341-374, 2012.
27. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. A new two-locus disease association pattern identified in genome-wide association studies, BMC Bioinformatics, 12:156, 2011. (co-first author)
28. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. The choice of null distributions for detecting gene-gene interactions in genome-wide association studies, BMC Bioinformatics, 12(Suppl 1):S26, 2011. (co-first author)
29. Lingxing Yung, Can Yang, Xiang Wan, Weichuan Yu. GBOOST: A GPU-Based Tool for Detecting Gene-Gene Interactions in Genome-Wide Case Control Studies, Bioinformatics, 28(1):145-146, 2011
30. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Xiaodan Fan, Nelson L.S. Tang, Weichuan Yu. BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies, American Journal of Human Genetics, 87(3), 325-340, 2010.
31. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Detecting two-locus associations allowing for interactions in genome-wide association studies, Bioinformatics, 26(20): 2517-2525, 2010.
32. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Predictive rule inference for epistatic interaction detection in genome-wide association study, Bioinformatics, 26(1):30-37, 2010.
33. Can Yang, Xiang Wan, Qiang Yang, Hong Xue, Weichuan Yu. Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group lasso, BMC Bioinformatics, 11(Suppl 1):S18, 2010.
34. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome-wide association study, BMC Bioinformatics, 10:13, 2009.
35. Kimberly L Stark, Bin Xu, Anindya Bagchi, Wen-Sung Lai, Hui Liu, Ruby Hsu, Xiang Wan, Paul Pavlidis, Alea A Mills, Maria Karayiorgou1 & Joseph A Gogos Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model, Nature Genetics, 40, 751 – 760, 2008.
36. Can Yang, Zengyou He, Xiang Wan, Weichuan Yu, Qiang Yang, Hong Xue, SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies, Bioinformatics, doi:10.1093, 2008.
37. Xiang Wan, Paul Pavlidis. Sharing and reusing gene expression profiling data in neuroscience, Neuroinformatics, 5(3), 161-175, 2007.
38. Xiang Wan, Guohui Lin. CISA: Combined NMR Resonance Connectivity Information Determination and Sequential Assignment, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(3), 336-348, 2007.
39. Xiang Wan, Guohui Lin. A Graph-Based Automated NMR Backbone Resonance Sequential Assignment, Journal of Bioinformatics and Computational Biology, 5(2), 313-333, 2007.
40. Guohui Lin, Xiang Wan, Theodos Tegos, Yingshu Li. Statistical Evaluation of NMR Backbone Resonance Assignment, International Journal of Bioinformatics Research and Applications, 2(2), 147-160, 2006.
41. Xiang Wan, Theodos Tegos, Guohui Lin. Histogram-based Scoring Schemes for Protein NMR Resonance Assignment, Journal of Bioinformatics and Computational Biology, 2.
POSITION/TITLE
Lab Director of Medical Big Data Laboratory
EDUCATION BACKGROUND
Ph.D. Computing Science, University of Alberta, 2006
M.S. Computing Science, University of Alberta, 2001
B.S. Information System, Renmin University, 1994
RESEARCH FIELD
Meta-analysis, Data Mining, Large-scale Genomic Data Analysis, High Performance Computing, Evidence-based Medicine
wanxiang@sribd.cn
BIOGRAPHY
Professor Wan received his BA in Information System from Renmin University and his MA and Ph.D. in Computing Science from University of Alberta. Professor Wan was a research assistant professor at Hong Kong Baptist University from 2012 to 2018. And he is now working concurrently as a research scientist at Shenzhen Research Institute of Big Data since 2018.
Professor Wan has been mainly working on meta-analysis and statistical learning, particularly in the field of large-scale genomic data analysis. He has published more than 40 papers in many top-tier journals, including Nature Genetics, American Journal of Human Genetics, BMC Genetics, Bioinformatics, BMC Bioinformatics, Neuro-informatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics, etc. Professor Wan is currently the director of Medical Big Data Lab. The main research goal of this lab is to integrate electronic medical records, medical imaging, health check reports and multi-omics data to help the pre-diagnosis and the personalized treatment.
ACADEMIC PUBLICATIONS
1. Can Yang, Xiang Wan*, Xinyi Lin, Mengjie Chen, Xiang Zhou, Jin Liu. CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information, Bioinformatics 35(10) 1644-1652, 2019. (co-first author)
2. Jingsi Ming, Mingwei Dai, Mingxuan Cai, Xiang Wan, Jin Liu, Can Yang. LSMM: a statistical approach to integrating functional annotations with genome-wide association studies. Bioinformatics, 2019, 34 (16), 2788-2796.
3. Mingwei Dai, Xiang Wan, Heng Peng, Yao Wang, Yue Liu, Jin Liu, Zongben Xu, Can Yang. Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy. Bioinformatics, 2019, Bioinformatics 35 (10), 1729-1736.
4. Lili Yue, Gaorong Li, Heng Lian, Xiang Wan. Regression adjustment for treatment effect with multicollinearity in high dimensions. Computational Statistics & Data Analysis, 2019, 134:17-35.
5. Guanying Wu, Xiang Wan*, Baohua Xu. A new estimation of protein-level false discovery rate. BMC Genomics, 2018, 2018 Aug 13;19 (Suppl 6):567. doi: 10.1186/s12864-018-4923-3. (co-first author)
6. Dehui Luo, Xiang Wan*, Jiming Liu, Tiejun Tong,Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range，Statistical methods in medical research， 2018， 27 (6), 1785-1805. (co-correspondence author)
7. Yan Zhou, Xiang Wan*, Baoxue Zhang, Tiejun Tong, Classifying next-generation sequencing data using a zero-inflated Poisson model, Bioinformatics，2018， 15;34(8):1329-1335. (co-correspondence author)
8. Jin Liu, Xiang Wan*, Chaolong Wang, Chao Yang, Xiaowen Zhou, Can Yang, LLR: A latent low-rank approach to colocalizing genetic risk variants in multiple GWAS,Bioinformatics, 2017, 33(24):3878-3886. (co-first author)
9. Mingwei Dai, Jingsi Ming, Mingxuan Cai, Jin Liu, Can Yang, Xiang Wan*, ZongbenXue, IGESS: A Statistical Approach to Integrating Individual-Level Genotype Data and Summary Statistics in Genome-Wide Association Studies, Bioinformatics,2017,33(18): 2882-2889. (co-correspondence author)
10. Bin Zhang, Xiang Wan*, Yuhao Dong, Dehui Luo, Jing Liu, Long Liang, Wenbo Chen, Xiaoning Luo, Xiaokai Mo, Lu Zhang, Wenhui Huang, Shufang Pei, Fusheng Ouyang, Baoliang Guo, Changhong Liang, Zhouyang Lian, Shuixing Zhang, Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children, Scientific Report, 2017 Jul 14;7(1):5368. (co-first author)
11. Yan Zhou, Baoxue Zhou, Tiejun Tong, Xiang Wan*. GD-RDA: A New Regularized Discriminant Analysis for High-Dimensional Data, Journal of Computational Biology, 2017,24 (11), 1099-1111. (correspondence author)
12. Kai Dong, Hongyu Zhao, Tiejun Tong, Xiang Wan*. NBLDA: Negative Binomial Linear Discriminant Analysis for RNA-Seq Data,BMC Bioinformatics,2016, 17(1):369. (co-correspondence author)
13. Ruixing Ming, Jiming Liu, William K.W. Cheung, Xiang Wan*. Stochastic Modeling of Infectious Diseases for Heterogeneous Populations. BMC Infectious Disease, 2016,5(1):107. (correspondence author)
14. Jin Liu, Xiang Wan, Shuangge Ma, Can Yang. EPS: An empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genes, Bioinformatics, 2016, 32(12):1856-64
15. Ben Teng, Can Yang, Jiming Liu, Zhipeng Cai, Xiang Wan*. Exploring the genetic patterns of complex diseases via the integrative genome-wide approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015, 13(3): 557-664. (correspondence author)
16. Xiang Wan, Wenqian Wang, Jiming Liu, Tiejun Tong. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC medical research methodology, 14 (1), 135, 2014.
17. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Learning to improve medical decision making from imbalanced data without a priori cost. BMC medical informatics and decision making, 14 (1), 1, 2014.
18. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Inferring Epidemic Network Topology from Surveillance Data. Plos ONE, 9(6):e100661, 2014.
19. Xiaowei Zhou, Jiming Liu, Xiang Wan*, Weichuan Yu. Piecewise-constant and low-rank approximation for identification of recurrent copy number variations. Bioinformatics, 30(14):1943-1949, 2014. (correspondence author)
20. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 230-235, 2013.
21. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies. IEEE/ACM Transactions on Computational Biology and Bioinformatics, (1): 207-212, 2013.
22. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. The complete compositional epistasis detection in genome-wide association studies, BMC Genetics, 14(1):7, 2013.
23. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 207-212, 2013.
24. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization, IEEE/ACM Transactions on Computational Biology and Bioinformatics , 10(1), 207-212, 2013.
25. Xiang Wan, Can Yang, Weichuan Yu. Comments on 'An empirical comparison of several recent epistatic interaction detection methods', Bioinformatics, 28(1):145-146, 2012.
26. Geng Cui, Man Leung Wong, Xiang Wan. Cost-Sensitive Learning via Priority Sampling to Improve the Return on Marketing and CRM. Journal of Management Information System, 29(1):341-374, 2012.
27. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. A new two-locus disease association pattern identified in genome-wide association studies, BMC Bioinformatics, 12:156, 2011. (co-first author)
28. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. The choice of null distributions for detecting gene-gene interactions in genome-wide association studies, BMC Bioinformatics, 12(Suppl 1):S26, 2011. (co-first author)
29. Lingxing Yung, Can Yang, Xiang Wan, Weichuan Yu. GBOOST: A GPU-Based Tool for Detecting Gene-Gene Interactions in Genome-Wide Case Control Studies, Bioinformatics, 28(1):145-146, 2011
30. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Xiaodan Fan, Nelson L.S. Tang, Weichuan Yu. BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies, American Journal of Human Genetics, 87(3), 325-340, 2010.
31. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Detecting two-locus associations allowing for interactions in genome-wide association studies, Bioinformatics, 26(20): 2517-2525, 2010.
32. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Predictive rule inference for epistatic interaction detection in genome-wide association study, Bioinformatics, 26(1):30-37, 2010.
33. Can Yang, Xiang Wan, Qiang Yang, Hong Xue, Weichuan Yu. Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group lasso, BMC Bioinformatics, 11(Suppl 1):S18, 2010.
34. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome-wide association study, BMC Bioinformatics, 10:13, 2009.
35. Kimberly L Stark, Bin Xu, Anindya Bagchi, Wen-Sung Lai, Hui Liu, Ruby Hsu, Xiang Wan, Paul Pavlidis, Alea A Mills, Maria Karayiorgou1 & Joseph A Gogos Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model, Nature Genetics, 40, 751 – 760, 2008.
36. Can Yang, Zengyou He, Xiang Wan, Weichuan Yu, Qiang Yang, Hong Xue, SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies, Bioinformatics, doi:10.1093, 2008.
37. Xiang Wan, Paul Pavlidis. Sharing and reusing gene expression profiling data in neuroscience, Neuroinformatics, 5(3), 161-175, 2007.
38. Xiang Wan, Guohui Lin. CISA: Combined NMR Resonance Connectivity Information Determination and Sequential Assignment, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(3), 336-348, 2007.
39. Xiang Wan, Guohui Lin. A Graph-Based Automated NMR Backbone Resonance Sequential Assignment, Journal of Bioinformatics and Computational Biology, 5(2), 313-333, 2007.
40. Guohui Lin, Xiang Wan, Theodos Tegos, Yingshu Li. Statistical Evaluation of NMR Backbone Resonance Assignment, International Journal of Bioinformatics Research and Applications, 2(2), 147-160, 2006.
41. Xiang Wan, Theodos Tegos, Guohui Lin. Histogram-based Scoring Schemes for Protein NMR Resonance Assignment, Journal of Bioinformatics and Computational Biology, 2.
POSITION/TITLE
Lab Director of Medical Big Data Laboratory
EDUCATION BACKGROUND
Ph.D. Computing Science, University of Alberta, 2006
M.S. Computing Science, University of Alberta, 2001
B.S. Information System, Renmin University, 1994
RESEARCH FIELD
Meta-analysis, Data Mining, Large-scale Genomic Data Analysis, High Performance Computing, Evidence-based Medicine
wanxiang@sribd.cn
BIOGRAPHY
Professor Wan received his BA in Information System from Renmin University and his MA and Ph.D. in Computing Science from University of Alberta. Professor Wan was a research assistant professor at Hong Kong Baptist University from 2012 to 2018. And he is now working concurrently as a research scientist at Shenzhen Research Institute of Big Data since 2018.
Professor Wan has been mainly working on meta-analysis and statistical learning, particularly in the field of large-scale genomic data analysis. He has published more than 40 papers in many top-tier journals, including Nature Genetics, American Journal of Human Genetics, BMC Genetics, Bioinformatics, BMC Bioinformatics, Neuro-informatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics, etc. Professor Wan is currently the director of Medical Big Data Lab. The main research goal of this lab is to integrate electronic medical records, medical imaging, health check reports and multi-omics data to help the pre-diagnosis and the personalized treatment.
ACADEMIC PUBLICATIONS
1. Can Yang, Xiang Wan*, Xinyi Lin, Mengjie Chen, Xiang Zhou, Jin Liu. CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information, Bioinformatics 35(10) 1644-1652, 2019. (co-first author)
2. Jingsi Ming, Mingwei Dai, Mingxuan Cai, Xiang Wan, Jin Liu, Can Yang. LSMM: a statistical approach to integrating functional annotations with genome-wide association studies. Bioinformatics, 2019, 34 (16), 2788-2796.
3. Mingwei Dai, Xiang Wan, Heng Peng, Yao Wang, Yue Liu, Jin Liu, Zongben Xu, Can Yang. Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy. Bioinformatics, 2019, Bioinformatics 35 (10), 1729-1736.
4. Lili Yue, Gaorong Li, Heng Lian, Xiang Wan. Regression adjustment for treatment effect with multicollinearity in high dimensions. Computational Statistics & Data Analysis, 2019, 134:17-35.
5. Guanying Wu, Xiang Wan*, Baohua Xu. A new estimation of protein-level false discovery rate. BMC Genomics, 2018, 2018 Aug 13;19 (Suppl 6):567. doi: 10.1186/s12864-018-4923-3. (co-first author)
6. Dehui Luo, Xiang Wan*, Jiming Liu, Tiejun Tong,Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range，Statistical methods in medical research， 2018， 27 (6), 1785-1805. (co-correspondence author)
7. Yan Zhou, Xiang Wan*, Baoxue Zhang, Tiejun Tong, Classifying next-generation sequencing data using a zero-inflated Poisson model, Bioinformatics，2018， 15;34(8):1329-1335. (co-correspondence author)
8. Jin Liu, Xiang Wan*, Chaolong Wang, Chao Yang, Xiaowen Zhou, Can Yang, LLR: A latent low-rank approach to colocalizing genetic risk variants in multiple GWAS,Bioinformatics, 2017, 33(24):3878-3886. (co-first author)
9. Mingwei Dai, Jingsi Ming, Mingxuan Cai, Jin Liu, Can Yang, Xiang Wan*, ZongbenXue, IGESS: A Statistical Approach to Integrating Individual-Level Genotype Data and Summary Statistics in Genome-Wide Association Studies, Bioinformatics,2017,33(18): 2882-2889. (co-correspondence author)
10. Bin Zhang, Xiang Wan*, Yuhao Dong, Dehui Luo, Jing Liu, Long Liang, Wenbo Chen, Xiaoning Luo, Xiaokai Mo, Lu Zhang, Wenhui Huang, Shufang Pei, Fusheng Ouyang, Baoliang Guo, Changhong Liang, Zhouyang Lian, Shuixing Zhang, Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children, Scientific Report, 2017 Jul 14;7(1):5368. (co-first author)
11. Yan Zhou, Baoxue Zhou, Tiejun Tong, Xiang Wan*. GD-RDA: A New Regularized Discriminant Analysis for High-Dimensional Data, Journal of Computational Biology, 2017,24 (11), 1099-1111. (correspondence author)
12. Kai Dong, Hongyu Zhao, Tiejun Tong, Xiang Wan*. NBLDA: Negative Binomial Linear Discriminant Analysis for RNA-Seq Data,BMC Bioinformatics,2016, 17(1):369. (co-correspondence author)
13. Ruixing Ming, Jiming Liu, William K.W. Cheung, Xiang Wan*. Stochastic Modeling of Infectious Diseases for Heterogeneous Populations. BMC Infectious Disease, 2016,5(1):107. (correspondence author)
14. Jin Liu, Xiang Wan, Shuangge Ma, Can Yang. EPS: An empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genes, Bioinformatics, 2016, 32(12):1856-64
15. Ben Teng, Can Yang, Jiming Liu, Zhipeng Cai, Xiang Wan*. Exploring the genetic patterns of complex diseases via the integrative genome-wide approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015, 13(3): 557-664. (correspondence author)
16. Xiang Wan, Wenqian Wang, Jiming Liu, Tiejun Tong. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC medical research methodology, 14 (1), 135, 2014.
17. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Learning to improve medical decision making from imbalanced data without a priori cost. BMC medical informatics and decision making, 14 (1), 1, 2014.
18. Xiang Wan, Jiming Liu, William Cheung, Tiejun Tong. Inferring Epidemic Network Topology from Surveillance Data. Plos ONE, 9(6):e100661, 2014.
19. Xiaowei Zhou, Jiming Liu, Xiang Wan*, Weichuan Yu. Piecewise-constant and low-rank approximation for identification of recurrent copy number variations. Bioinformatics, 30(14):1943-1949, 2014. (correspondence author)
20. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 230-235, 2013.
21. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies. IEEE/ACM Transactions on Computational Biology and Bioinformatics, (1): 207-212, 2013.
22. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. The complete compositional epistasis detection in genome-wide association studies, BMC Genetics, 14(1):7, 2013.
23. Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu. HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(1): 207-212, 2013.
24. Xiaowei Zhou, Can Yang, Xiang Wan, Hongyu Zhao, Weichuan Yu. Multisample aCGH Data Analysis via Total Variation and Spectral Regularization, IEEE/ACM Transactions on Computational Biology and Bioinformatics , 10(1), 207-212, 2013.
25. Xiang Wan, Can Yang, Weichuan Yu. Comments on 'An empirical comparison of several recent epistatic interaction detection methods', Bioinformatics, 28(1):145-146, 2012.
26. Geng Cui, Man Leung Wong, Xiang Wan. Cost-Sensitive Learning via Priority Sampling to Improve the Return on Marketing and CRM. Journal of Management Information System, 29(1):341-374, 2012.
27. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. A new two-locus disease association pattern identified in genome-wide association studies, BMC Bioinformatics, 12:156, 2011. (co-first author)
28. Can Yang*, Xiang Wan*, Qiang Yang, Hong Xue, Weichuan Yu. The choice of null distributions for detecting gene-gene interactions in genome-wide association studies, BMC Bioinformatics, 12(Suppl 1):S26, 2011. (co-first author)
29. Lingxing Yung, Can Yang, Xiang Wan, Weichuan Yu. GBOOST: A GPU-Based Tool for Detecting Gene-Gene Interactions in Genome-Wide Case Control Studies, Bioinformatics, 28(1):145-146, 2011
30. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Xiaodan Fan, Nelson L.S. Tang, Weichuan Yu. BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies, American Journal of Human Genetics, 87(3), 325-340, 2010.
31. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Detecting two-locus associations allowing for interactions in genome-wide association studies, Bioinformatics, 26(20): 2517-2525, 2010.
32. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. Predictive rule inference for epistatic interaction detection in genome-wide association study, Bioinformatics, 26(1):30-37, 2010.
33. Can Yang, Xiang Wan, Qiang Yang, Hong Xue, Weichuan Yu. Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group lasso, BMC Bioinformatics, 11(Suppl 1):S18, 2010.
34. Xiang Wan, Can Yang, Qiang Yang, Hong Xue, Nelson L.S. Tang, Weichuan Yu. MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome-wide association study, BMC Bioinformatics, 10:13, 2009.
35. Kimberly L Stark, Bin Xu, Anindya Bagchi, Wen-Sung Lai, Hui Liu, Ruby Hsu, Xiang Wan, Paul Pavlidis, Alea A Mills, Maria Karayiorgou1 & Joseph A Gogos Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model, Nature Genetics, 40, 751 – 760, 2008.
36. Can Yang, Zengyou He, Xiang Wan, Weichuan Yu, Qiang Yang, Hong Xue, SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies, Bioinformatics, doi:10.1093, 2008.
37. Xiang Wan, Paul Pavlidis. Sharing and reusing gene expression profiling data in neuroscience, Neuroinformatics, 5(3), 161-175, 2007.
38. Xiang Wan, Guohui Lin. CISA: Combined NMR Resonance Connectivity Information Determination and Sequential Assignment, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(3), 336-348, 2007.
39. Xiang Wan, Guohui Lin. A Graph-Based Automated NMR Backbone Resonance Sequential Assignment, Journal of Bioinformatics and Computational Biology, 5(2), 313-333, 2007.
40. Guohui Lin, Xiang Wan, Theodos Tegos, Yingshu Li. Statistical Evaluation of NMR Backbone Resonance Assignment, International Journal of Bioinformatics Research and Applications, 2(2), 147-160, 2006.
41. Xiang Wan, Theodos Tegos, Guohui Lin. Histogram-based Scoring Schemes for Protein NMR Resonance Assignment, Journal of Bioinformatics and Computational Biology, 2.
POSITION/TITLE
Research Scientist
Assistant Professor
RESEARCH FIELD
Natural Language Processing, Information Retrieval, Applied Machine Learning, Quantum Machine Learning
wangbenyou@cuhk.edu.cn
PERSONAL WEBSITE
https://wabyking.github.io/old.html
EDUCATION BACKGROUND
Ph.D. Information Engineering (Information Science and Technology), University of Padua, 2022
M.Eng. Pattern Recognition and Intelligent Systems, Tianjin University, 2017
B.Eng. Software Engineering, Hubei University of Automotive Technology, 2014
Major Achievements/Honors
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award
BIOGRAPHY
Benyou Wang received Ph.D. degree at the University of Padua, Italy, funded by the Marie Curie Fellowship. He obtained a master's degree from Tianjin University. In his research career, he has visited University of Copenhagen (Denmark), University of Montreal (Canada), University of Amsterdam (the Netherlands), Huawei Noah's Ark Laboratory (Shenzhen, China), Institute of Theoretical Physics (Chinese Academy of Sciences, Beijing China), and Language Institute (Chinese Academy of Social Sciences, Beijing, China). He is committed to building explainable, robust, and efficient natural language processing approaches that are with both technical rationality and linguistic motivation. So far, he and his collaborators have won the Best Paper Nomination Award in SIGIR 2017 (the top conference in information retrieval) and Best Explainable NLP Paper in NAACL 2019 (a top conference on natural language processing). He had many articles in top international conferences NeurIPS/ICLR/SIGIR/WWW/NAACL and top international journals such as IEEE Transactions on Information System (TOIS), IEEE Transaction on Cybernetics (TOC), and Theoretical Computer Science (TCS). According to Google Scholar, he had achieved nearly 1000 citations with an h-index of 16 when he receives his Ph.D. degree.
ACADEMIC PUBLICATIONS
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI Q1 top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
POSITION/TITLE
Research Scientist
Assistant Professor
RESEARCH FIELD
Natural Language Processing, Information Retrieval, Applied Machine Learning, Quantum Machine Learning
wangbenyou@cuhk.edu.cn
PERSONAL WEBSITE
https://wabyking.github.io/old.html
EDUCATION BACKGROUND
Ph.D. Information Engineering (Information Science and Technology), University of Padua, 2022
M.Eng. Pattern Recognition and Intelligent Systems, Tianjin University, 2017
B.Eng. Software Engineering, Hubei University of Automotive Technology, 2014
Major Achievements/Honors
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award
BIOGRAPHY
Benyou Wang received Ph.D. degree at the University of Padua, Italy, funded by the Marie Curie Fellowship. He obtained a master's degree from Tianjin University. In his research career, he has visited University of Copenhagen (Denmark), University of Montreal (Canada), University of Amsterdam (the Netherlands), Huawei Noah's Ark Laboratory (Shenzhen, China), Institute of Theoretical Physics (Chinese Academy of Sciences, Beijing China), and Language Institute (Chinese Academy of Social Sciences, Beijing, China). He is committed to building explainable, robust, and efficient natural language processing approaches that are with both technical rationality and linguistic motivation. So far, he and his collaborators have won the Best Paper Nomination Award in SIGIR 2017 (the top conference in information retrieval) and Best Explainable NLP Paper in NAACL 2019 (a top conference on natural language processing). He had many articles in top international conferences NeurIPS/ICLR/SIGIR/WWW/NAACL and top international journals such as IEEE Transactions on Information System (TOIS), IEEE Transaction on Cybernetics (TOC), and Theoretical Computer Science (TCS). According to Google Scholar, he had achieved nearly 1000 citations with an h-index of 16 when he receives his Ph.D. degree.
ACADEMIC PUBLICATIONS
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI Q1 top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
POSITION/TITLE
Research Scientist
Assistant Professor
RESEARCH FIELD
Natural Language Processing, Information Retrieval, Applied Machine Learning, Quantum Machine Learning
wangbenyou@cuhk.edu.cn
PERSONAL WEBSITE
https://wabyking.github.io/old.html
EDUCATION BACKGROUND
Ph.D. Information Engineering (Information Science and Technology), University of Padua, 2022
M.Eng. Pattern Recognition and Intelligent Systems, Tianjin University, 2017
B.Eng. Software Engineering, Hubei University of Automotive Technology, 2014
Major Achievements/Honors
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award
BIOGRAPHY
Benyou Wang received Ph.D. degree at the University of Padua, Italy, funded by the Marie Curie Fellowship. He obtained a master's degree from Tianjin University. In his research career, he has visited University of Copenhagen (Denmark), University of Montreal (Canada), University of Amsterdam (the Netherlands), Huawei Noah's Ark Laboratory (Shenzhen, China), Institute of Theoretical Physics (Chinese Academy of Sciences, Beijing China), and Language Institute (Chinese Academy of Social Sciences, Beijing, China). He is committed to building explainable, robust, and efficient natural language processing approaches that are with both technical rationality and linguistic motivation. So far, he and his collaborators have won the Best Paper Nomination Award in SIGIR 2017 (the top conference in information retrieval) and Best Explainable NLP Paper in NAACL 2019 (a top conference on natural language processing). He had many articles in top international conferences NeurIPS/ICLR/SIGIR/WWW/NAACL and top international journals such as IEEE Transactions on Information System (TOIS), IEEE Transaction on Cybernetics (TOC), and Theoretical Computer Science (TCS). According to Google Scholar, he had achieved nearly 1000 citations with an h-index of 16 when he receives his Ph.D. degree.
ACADEMIC PUBLICATIONS
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI Q1 top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
POSITION/TITLE
Research Scientist
Assistant Professor
RESEARCH FIELD
Natural Language Processing, Information Retrieval, Applied Machine Learning, Quantum Machine Learning
wangbenyou@cuhk.edu.cn
PERSONAL WEBSITE
https://wabyking.github.io/old.html
EDUCATION BACKGROUND
Ph.D. Information Engineering (Information Science and Technology), University of Padua, 2022
M.Eng. Pattern Recognition and Intelligent Systems, Tianjin University, 2017
B.Eng. Software Engineering, Hubei University of Automotive Technology, 2014
Major Achievements/Honors
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award
BIOGRAPHY
Benyou Wang received Ph.D. degree at the University of Padua, Italy, funded by the Marie Curie Fellowship. He obtained a master's degree from Tianjin University. In his research career, he has visited University of Copenhagen (Denmark), University of Montreal (Canada), University of Amsterdam (the Netherlands), Huawei Noah's Ark Laboratory (Shenzhen, China), Institute of Theoretical Physics (Chinese Academy of Sciences, Beijing China), and Language Institute (Chinese Academy of Social Sciences, Beijing, China). He is committed to building explainable, robust, and efficient natural language processing approaches that are with both technical rationality and linguistic motivation. So far, he and his collaborators have won the Best Paper Nomination Award in SIGIR 2017 (the top conference in information retrieval) and Best Explainable NLP Paper in NAACL 2019 (a top conference on natural language processing). He had many articles in top international conferences NeurIPS/ICLR/SIGIR/WWW/NAACL and top international journals such as IEEE Transactions on Information System (TOIS), IEEE Transaction on Cybernetics (TOC), and Theoretical Computer Science (TCS). According to Google Scholar, he had achieved nearly 1000 citations with an h-index of 16 when he receives his Ph.D. degree.
ACADEMIC PUBLICATIONS
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI Q1 top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
POSITION/TITLE
SRIBD, Medical Big Data Lab, Research Scientist
RESEARCH FIELD
Bioinformatics, Genome-wide association analysis (GWAS), statistical and machine learning methods for spatial transcriptome and multi-omics data
xiaojiashun@sribd.cn
EDUCATION BACKGROUND
Ph.D. in Mathematics, Hong Kong University of Science and Technology, 2018-2022
B.S. in Bioinformatics, Southern University of Science and Technology, 2013-2017
BIOGRAPHY
Dr. Xiao Jiashun is currently a research scientist in the Medical Big Data Laboratory of Shenzhen Institute of Big Data Research. He received a Ph.D. in Mathematics from Hong Kong University of Science and Technology in 2022, and a Bachelor's degree in Bioinformatics from Southern University of Science and Technology in 2017. He joined WeGene as a bioinformatics engineer from 207 to 2018. His research aims to develop statistical and machine learning methods for multi-omics data, including trans-ancestry association mapping, polygenic prediction with large-scale genetic data, and integrative analysis of single-cell and spatial transcriptomics data, etc. He has published several papers in international academic journals (AJHG, Bioinformatics, etc.) as the first or co-first author.
ACADEMIC PUBLICATIONS
Xiao, J.#, Cai, M.#, Yu, X., Hu, X., Chen, G., Wan, X., & Yang, C. (2022). Leveraging the local genetic structure for trans-ancestry association mapping. The American Journal of Human Genetics, 109(7), 1317-1337.
Xiao, J.#, Cai, M.#, Hu, X., Wan, X., Chen, G., & Yang, C. (2022). XPXP: Improving polygenic prediction by cross-population and cross-phenotype analysis. Bioinformatics, 38(7), 1947-1955.
Cai, M#., Xiao, J#., Zhang, S#., Wan, X., Zhao, H., Chen, G., & Yang, C. (2021). A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits. The American Journal of Human Genetics, 108(4), 632-655.
Yu X., Xiao J., Cai M., Jiao Y., Wan X., Liu J., Yang C. (2023). PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations. Bioinformatics, 39(2).
Yiming Chao, Yang Xiang, Jiashun Xiao, et al. (2023). Organoid-based single-cell spatiotemporal gene expression landscape of human embryonic development and hematopoiesis. Signal Transduction and Targeted Therapy, Under minor revision.
# co-first author
POSITION/TITLE
SRIBD, Medical Big Data Lab, Research Scientist
RESEARCH FIELD
Bioinformatics, Genome-wide association analysis (GWAS), statistical and machine learning methods for spatial transcriptome and multi-omics data
xiaojiashun@sribd.cn
EDUCATION BACKGROUND
Ph.D. in Mathematics, Hong Kong University of Science and Technology, 2018-2022
B.S. in Bioinformatics, Southern University of Science and Technology, 2013-2017
BIOGRAPHY
Dr. Xiao Jiashun is currently a research scientist in the Medical Big Data Laboratory of Shenzhen Institute of Big Data Research. He received a Ph.D. in Mathematics from Hong Kong University of Science and Technology in 2022, and a Bachelor's degree in Bioinformatics from Southern University of Science and Technology in 2017. He joined WeGene as a bioinformatics engineer from 207 to 2018. His research aims to develop statistical and machine learning methods for multi-omics data, including trans-ancestry association mapping, polygenic prediction with large-scale genetic data, and integrative analysis of single-cell and spatial transcriptomics data, etc. He has published several papers in international academic journals (AJHG, Bioinformatics, etc.) as the first or co-first author.
ACADEMIC PUBLICATIONS
Xiao, J.#, Cai, M.#, Yu, X., Hu, X., Chen, G., Wan, X., & Yang, C. (2022). Leveraging the local genetic structure for trans-ancestry association mapping. The American Journal of Human Genetics, 109(7), 1317-1337.
Xiao, J.#, Cai, M.#, Hu, X., Wan, X., Chen, G., & Yang, C. (2022). XPXP: Improving polygenic prediction by cross-population and cross-phenotype analysis. Bioinformatics, 38(7), 1947-1955.
Cai, M#., Xiao, J#., Zhang, S#., Wan, X., Zhao, H., Chen, G., & Yang, C. (2021). A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits. The American Journal of Human Genetics, 108(4), 632-655.
Yu X., Xiao J., Cai M., Jiao Y., Wan X., Liu J., Yang C. (2023). PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations. Bioinformatics, 39(2).
Yiming Chao, Yang Xiang, Jiashun Xiao, et al. (2023). Organoid-based single-cell spatiotemporal gene expression landscape of human embryonic development and hematopoiesis. Signal Transduction and Targeted Therapy, Under minor revision.
# co-first author
POSITION/TITLE
SRIBD, Medical Big Data Lab, Research Scientist
RESEARCH FIELD
Bioinformatics, Genome-wide association analysis (GWAS), statistical and machine learning methods for spatial transcriptome and multi-omics data
xiaojiashun@sribd.cn
EDUCATION BACKGROUND
Ph.D. in Mathematics, Hong Kong University of Science and Technology, 2018-2022
B.S. in Bioinformatics, Southern University of Science and Technology, 2013-2017
BIOGRAPHY
Dr. Xiao Jiashun is currently a research scientist in the Medical Big Data Laboratory of Shenzhen Institute of Big Data Research. He received a Ph.D. in Mathematics from Hong Kong University of Science and Technology in 2022, and a Bachelor's degree in Bioinformatics from Southern University of Science and Technology in 2017. He joined WeGene as a bioinformatics engineer from 207 to 2018. His research aims to develop statistical and machine learning methods for multi-omics data, including trans-ancestry association mapping, polygenic prediction with large-scale genetic data, and integrative analysis of single-cell and spatial transcriptomics data, etc. He has published several papers in international academic journals (AJHG, Bioinformatics, etc.) as the first or co-first author.
ACADEMIC PUBLICATIONS
Xiao, J.#, Cai, M.#, Yu, X., Hu, X., Chen, G., Wan, X., & Yang, C. (2022). Leveraging the local genetic structure for trans-ancestry association mapping. The American Journal of Human Genetics, 109(7), 1317-1337.
Xiao, J.#, Cai, M.#, Hu, X., Wan, X., Chen, G., & Yang, C. (2022). XPXP: Improving polygenic prediction by cross-population and cross-phenotype analysis. Bioinformatics, 38(7), 1947-1955.
Cai, M#., Xiao, J#., Zhang, S#., Wan, X., Zhao, H., Chen, G., & Yang, C. (2021). A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits. The American Journal of Human Genetics, 108(4), 632-655.
Yu X., Xiao J., Cai M., Jiao Y., Wan X., Liu J., Yang C. (2023). PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations. Bioinformatics, 39(2).
Yiming Chao, Yang Xiang, Jiashun Xiao, et al. (2023). Organoid-based single-cell spatiotemporal gene expression landscape of human embryonic development and hematopoiesis. Signal Transduction and Targeted Therapy, Under minor revision.
# co-first author
