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Biology is rapidly transforming into a big data field. We can now readily generate huge amounts of data describing genomes, epigenomes, transcriptomes, protein structures and complex signaling networks. This has created an unprecedented demand for a new generation of interdisciplinary scientists. In Bioinformatics and Computational Biology, we apply mathematics, computer science, statistics and engineering methods in new ways to complex biological data. By leveraging new technology and new analytical approaches, we seek to answer fundamental questions about living organisms and make breakthrough scientific discoveries.
The Bioinformatics and Computational Biology faculty at UMMS develop and apply computational and statistical methods to study a variety of biological problems, with an emphasis on high-throughput DNA, RNA, and protein data. We use computation and mathematics to analyze regulatory and metabolic networks; explore the structure of the genome; deduce the evolutionary history and function of DNA, RNA, and proteins using comparative genomics; apply population genetics and molecular evolution to problems of human health; probe large-scale protein-protein, protein-DNA, and protein-RNA interactions; and model large biological systems in silico. Jeffrey Bailey’s lab studies genomics, molecular genetics, and infectious diseases. Manuel Garber’s lab studies genomics, epigenomics, and transcriptional regulation. Elinor Karlsson’s lab studies genomics, mammalian genetics, infectious diseases, and molecular evolution. Zhiping Weng’s lab studies genomics, epigenomics, transcriptional regulation, and RNA biology. Konstantin Zeldovich’s lab studies molecular evolution and infectious diseases. Together, our research bridges the gap between wet-lab biologists and computational scientists, and prepares students for careers in cutting-edge, highly quantitative, biomedical research.
For more information please see: http://www.umassmed.edu/gsbs/academics/bioinformatics--computational-biology/program-overview/