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    Rensselaer Polytechnic Institute
  Aug 18, 2017
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Rensselaer Catalog 2017-2018

Bioinformatics and Molecular Biology

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Director, Undergraduate and Graduate Degree Programs: Chris Bystroff

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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 high throughput gene sequencing an integral part of the scientific landscape. Numerous genome-sequencing projects have produced complete sequences of viruses, bacteria, and increasingly complex eukaryotic organisms. The complete human genome was completed in 2003, with 20,000 genes and 3 billion base pairs. Today thousands of human genomes and the genomes of thousands of organisms have been sequenced.
The enormous treasure trove of information that the sequence databases and their 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.

Undergraduate Program

Rensselaer’s bioinformatics and molecular biology undergraduate curriculum includes training in mathematics, chemistry, computer science, and physics. At the program’s core are courses in the theory and practice of sequence analysis, including database search algorithms, alignment, molecular evolution, RNA structure, systems dynamics and phylogenetics; and molecular modeling, including comparative modeling of proteins, docking, sequence analysis, molecular dynamics, protein design, and drug design. The experimental side includes courses in molecular biology, biochemistry, and genomics.

An extensive list of electives allows students to focus their interests towards depth in either computational methods or in experimental methods. Dual majors with computer science, biochemistry and biophysics, or mathematics are easily accommodated. The bioinformatics and molecular biology program also serves as an excellent premedical curriculum.

As a culminating experience, this major requires a senior thesis, which can be experimental or computational laboratory research, either independently or as a team, or literature research on a suitable topic.

Outcomes of the Undergraduate Curriculum
Students who successfully complete this program will be able to demonstrate:

  • an ability to apply knowledge of mathematics and computer science.
  • knowledge of the origins and usage of biological databases.
  • an ability to communicate and collaborate with other disciplines, knowledge of interdisciplinary connections, and knowledge of the relationship between science and society. 
  • knowledge of biological evolution.
  • knowledge of the flow, exchange and storage of genetic information.
  • knowledge of the structure function relationship in biology.
  • an ability to research, prepare, communicate, and present results.

Associated Graduate Programs

The Master of Science in Biology with a concentration in bioinformatics is available for those desiring an M.S. degree before proceeding to professional work or doctoral programs. It is possible to enter the doctoral programs in Biology, Biochemistry and Biophysics, or Computer Science with a concentration in bioinformatics.

Research Innovations and Initiatives

There are extensive opportunities for bioinformatics and molecular biology majors to pursue undergraduate research in faculty laboratories, sometimes adding a computational capacity to experimental labs, and sometimes by serving as a bridge between computational and experimental biology. Several experimental research programs have benefited from undergraduate researchers who are trained in sequence analysis, molecular modeling, and database design. 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.

Research in computational biology is funded by a diverse group of agencies including NIH, NSF, the American Diabetes Association, and NASA. Computational biology research projects range from data mining, machine learning, molecular dynamics, drug discovery, chemoinformatics, enzymology, signal transduction, protein engineering, protein folding, protein design, biosensing, systems dynamics, phylogenetics, and studies on environmental adaptations of microorganisms.


Biology: C. Bystroff, S. Gilbert, L. Ligon, D. Swank, B. Barquera, G. Makhatadze, C. Wang, P. Maxwell, S. Nierzwicki-Bauer, D. Crone, J. Hurley, K. Rose, C. Royer

Computer Science: B. Szymanski, M. Zaki

Chemistry and Chemical Biology: C. Breneman, W. Colon, R. Lindhart, K. Lakshmi, L. McGown, X. Wang

Mathematical Sciences: Bennett; P. Drineas, P. Kramer

Chemical and Biological Engineering: J. Dordick, S. Garde, M . Koffas, R. Kane, P. Tessier, C. Collins, P. Karande

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