Computational Biology

A substantial core of computational biology (or bioinformatics) methods has been developed during the past two decades to meet the need of biological scientists for understanding experimental data and linking it to molecular mechanisms and to public health. These range from early motivating problems in DNA and protein sequence analysis to more recent advances in transcriptomics, epigenetics, and high-throughput projects such as the Human Genome Project, ENCODE, The Cancer Genome Atlas, and the Human Microbiome Project. The scope of bioinformatics research has thus been extended to embrace diverse topics such as microarray analysis, protein classification, regulatory motif analysis, RNA analysis, structural and functional predictions, gene prediction, molecular epidemiology, and personal genomics. The field is highly interdisciplinary in nature and requires knowledge of computational algorithms, statistics, and molecular biology. The faculties and students in this department are actively exploring and pushing the frontiers of these fields.


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