Center for Biomolecular and Medical Informatics (CBMI)
The Center for Biomolecular and Medical Informatics provides a regional and national resource in biomedical computation, which includes bioinformatics, cheminformatics, computational biology and computational chemistry, for companies in biotechnology, genomics, drug discovery, computer software and hardware development.
The mission is to provide a scientifically excellent, enriched, and practical educational experience for undergraduate and graduate students aspiring to work in the area of biomedical computing, computational molecular biology and the new fields of bioinformatics and cheminformatics.
In addition to supporting the accredited academic programs, the Center develops professional educational courses and seminars in “best practice” knowledge and skills for a new workforce in biomedical computing.
These efforts are undertaken in close affiliation with industry partners and the UMass Medical School. An Advisory Board composed of industry executives and educational leaders helps to set priorities and direction for the Center’s research programs and educational initiatives.
The Center draws strength from affiliated faculty and research fellows in computer science, biology, chemistry, mathematics and philosophy (bioethics), focused on the integrated application of knowledge to bioinformatics and cheminformatics and computational molecular biology and chemistry.
The implications are important first, for mining knowledge from the increasingly large informational datasets produced by genomic, medical, health and related applications; and second for the development of new computer applications for drug discovery in the pharmaceutical industry, which provide a more fundamental molecular view of how organisms use intracellular structure and process to carry out biological function.
Center strengths include the integration of distributed database designs, parallel and high performance applied algorithms, computational geometry, high dimensional visualization and data mining. These computational techniques are applied to large datasets, including genomic, proteomic and chemical databases.
For Information Contact
Dr. Georges Grinstein, Director