Computational Biology and Drug Design (CBDD) Group develops and implements new concepts, algorithms and software for rapid identification of bioactive compounds and pharmaceutical lead structures, and rapid diagnosis and evaluation of complex disease systems. The molecular design cycle involves multiple scientific disciplines and requires rigorous trans-disciplinary thinking. We employ a broad repertoire of machine-learning methods and bio/cheminformatics techniques for automated hypothesis generation, activity prediction and validation. The disease diagnosis aims at studying the relationship between disease phenotype and various omics (genomics, transcriptomics, proteomics, metabolomics, and phenomics), and involves the integration analysis of multi-level omics. We employ a broad repertoire of artificial intelligent methods and bioinformatics/systems biology techniques for automated hypothesis generation, disease diagnosis and biomarker discovery.
1: The development and application of new artificial intelligent and machine learning algorithms in drug discovery
2: Artificial intelligent-based and systems pharmacology-based computer-assisted molecular design
3: Large-scale computational study of the relationship between phenomics and genomics in complex disease systems
4: The development of software, web service and database in systems biology and drug discovery
Alma Mater:Central South University