Bioinformatics and Computational Biology

Bioinformatics involves the specific algorithmic designs and machine learning techniques to process and analyze bioological data, modeling biological problems. It has high impacts on our health, life, and society. The tools and models from this area significantly advance the understanding of life and improve life qualities. Specifically, computer science intensively contributed to large-scale projects, such as Human Genome Project, Human Brain Project, and Human Microbiome Project. On the other hand, many startup companies are also fostered by bioinformatics.

Our department has an active bioinformatics research program; we study a range of exciting and essential problems by developing solid algorithmic and machine-learning techniques and tools; for instance, gene network inference relies upon causality analysis to infer gene interactions from microarray or RNA-seq data. Protein structure prediction adopts deep learning to infer the 3D tertiary structure from an amino acid sequence. Haplotype inferences adopted the graph theory to resolve our diploid genomes from sequencing data. The vaccine designs learn the patterns embedded in nucleic acid data to enable efficient RNA vaccine design. Cancer genome analysis integrate multi-omics data with tensor computing to decipher the cancer heterogeneity for clinical impacts.