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Computational Biology

As the twentieth century drew to a close, the branches of science undergoing the most rapid change were biology (where new molecular insights were revolutionizing our understanding of living systems) and computer science (in which technological and conceptual breakthroughs were creating an unprecedented increase in our ability to gather, store, and analyze data). A natural outcome of this situation was the formation of a new field, bioinformatics, in which computers are applied to the challenges of deepening our understanding of life science.

UMBC has an established and growing interest in bioinformatics. Within the department of Biological Sciences, four faculty members have research groups dedicated to bioinformatics, and numerous other faculty use a significant computing component within their research (from phylogenetic reconstruction to sequence alignment and structural investigations). More important, UMBC is deeply committed to a future of interdepartmental and interdisciplinary research that is crucial to this emerging frontier of research. As such we have active and growing bioinformatics connections to the departments of Mathematics and Statistics, Chemistry and Biochemistry, Computer Science, and the School of Engineering.

Faculty with Interest in Computational Biology:

Bustos, Mauricio
We conduct research on the development of hierarchies within multi-agent system communities, and stochastic modeling of network phenomena.

Erill, Ivan
Application of soft-computing paradigms to open questions in genomics, focusing primarily on regulation. Research into DNA-binding site identification.

Kann, Maricel
Computational approaches for the detection of protein domains and protein interactions, and bioinformatics methodologies to understand the molecular basis of diseases.

Lobo, Daniel
Computational systems that understand, control, and design complex biological processes such as the regulation of development and regeneration, the formation of cancer and other diseases, and the applications of synthetic biology.