Project description/goals

The availability of massive amount of COVID-19 research data has brought both new opportunities and challenges. These research data, as well as other related data (i.e., immunological, organismal structural data, and so on), especially for viruses in the coronavirus family similar to SARS-CoV-2, urgently need a dedicated system to compile and organize them in an integrated manner. And such a system will facilitate the application-driven scientific research. This project will address this demand and use this platform to guide vaccine development and drug design through intelligent analysis of biological big data. 

Importance/impact, challenges/pain points

The currently existing databases storing SARS-CoV-2 information are not designed to handle information from immunological studies and cannot integrate this information with genomic sequence and protein structure data. In addition, the format of the data in these databases is not uniform and there is currently no platform available to identify and integrate all relevant information in these databases. 

Solution description

Designing a methodology for virus sequence analysis, developing a web platform to integrate publicly available datasets and embedding our designed analysis methodology

Key contribution/commercial implication

This project will provide a platform for the development of an automatic analysis of biological big data for sequence analysis, target prediction, effective diagnosis and evaluation, and drug design for COVID-19. The platform consists of four aspects: (1) fast and real-time integration of shared data related to COVID-19 published by various international collaborative projects and organizations; (2) analytical tools for the study of COVID-19 and rational design of vaccine candidates; (3) assistance in the diagnosis and treatment process of COVID-19; and (4) assistance for the research task of developing antiviral drugs against COVID-19.

Next steps

Relevant scientific model design and validation has been completed, and we are developing a new web-based coronavirus analysis platform for centralizing and integrating various biological data related to COVID-19, combined with visualization, analysis and interpretation mechanisms. The main framework of this platform has been built. Other related modules are being implemented one by one.

Collaborators/partners

Hong Kong University of Science and Technology

Team/contributors

Zhiquan Luo，‪Matthew R. McKay‬，Xiang Wan，Zhen Li，Li Liu