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Director, Undergraduate and Graduate Degree Programs: Chris Bystroff
Program Home Page: http://j2ee.rpi.edu/biology/update.do
Revolutions in biotechnology and information technology are changing the world. Advances in molecular genetics, coupled with improved capability in robotics, computer science, and other technologies, have made mass sequencing of genetic material a part of the scientific landscape. Previously, growing sequence databases had been compiled one gene at a time by individual research laboratories. This cottage industry approach is still part of the effort, but numerous genome-sequencing projects have produced the entire sequences of viruses, bacteria, and increasingly complex eukaryotic organisms. The complete human genome with its 109 base pairs is now complete.
The enormous treasure trove of information that the sequence databases and their smaller structural counterparts represent is a priceless resource. Applications include the identification of targets for drug discovery, the study of structural and functional relationships, and work on molecular evolution. Timely advances in computer science have made the storage, organization, and utilization of these very large data collections possible.
Bioinformatics approaches incorporate expertise from the biological sciences, computer science, and mathematics. Allied computational approaches using chemical and physical methods are also of widespread interest. Rensselaer’s bioinformatics and molecular biology undergraduate curriculum includes training in mathematics, chemistry, and physics. At the program’s core are courses in the theory and practice of bioinformatics that deal with topics such as database design and search algorithms, sequence alignment, sequence analysis, and molecular modeling. The core includes a molecular biology sequence and training in drug discovery.
The curriculum is extremely flexible, allowing for dual majors with several other disciplines including computer science. Advanced courses are available through the biology program and the biochemistry and biophysics program, including a strong set of advanced laboratory courses. Through appropriate elective selection, students planning careers as molecular biologists with a computational background or as fully trained computer scientists with a knowledge of biological sciences can adapt the program to their needs.
There are extensive opportunities to pursue undergraduate research in faculty laboratories. The bioinformatics and molecular biology program also serves as an excellent premedical curriculum.
Research Innovations and Initiatives
Bioinformatics research at Rensselaer includes the design and application of algorithms for sequence database searching, sequence alignment, and sequence analysis, molecular modeling, and allied areas in computational chemistry and simulation of biological processes. Closely related research in molecular genetics and biochemistry provides concrete applications for graduate and undergraduate students. A diverse group of agencies including NIH, NSF, the American Diabetes Association, and NASA fund this work. Research projects range from drug discovery, enzymology, signal transduction, protein structure, and protein folding to studies on environmental adaptations of microorganisms.
The primary goal of the of the master’s degree program in this field is to educate students for jobs in biotechnology, pharmaceuticals, and related industry sectors. The professional Master of Science in Applied Science program with a concentration in bioinformatics is also available to those wishing to upgrade their skills while employed in industry. The Master of Science in biology with a concentration in bioinformatics may attract those desiring an M.S. degree before proceeding to professional study in medicine or an allied health field. It may also be useful to students with a B.S. degree in biological sciences who wish to prepare for eventual entry in to a doctoral program at Rensselaer or elsewhere. It is possible to enter the doctoral program in biology with a concentration in bioinformatics.
Biology: C. Bystroff, J. Diwan, A.Garcia, J.F. Koretz
Chemistry and Chemical Biology: C.M. Breneman, W. Colon, M. Wentland
Computer and Information Science at Hartford: H. Younessi
Computer Science: B.K. Szymanski, M.Zaki
Decision Sciences and Engineering Systems: M.J. Embrechts
Mathematical Sciences: M. Zuker
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