The School of Computer Science and Mellon College of Science have joined forces to establish an exciting new interdisciplinary program leading to a B.S. in Computational Biology. This new degree is a major re-engineering of the current Computational Biology major offered by the department of Biological Sciences (which was the first degree-granting program in Computational Biology in the country). This new degree supplants the old program beginning this year.
The goal of this new degree program is to provide an intensive interdisciplinary education to enable outstanding students to become leaders in identifying and solving tomorrow's biological problems using computational methods. The new program's curriculum is truly interdisciplinary and is designed for students interested in the intersection of Biology and Computer Science.
Applications to the program are invited from current sophomores. Applicants must have completed, or be currently enrolled in: 03-231, Biochemistry I and 15-211, Fundamental Data Structures and Algorithms (for exceptions contact Amy Burkert (MCS students) or Mark Stehlik (SCS students)). Applicants must submit an informal transcript (whiteprint, obtainable from their academic advisor) and an essay of one page that describes why you want to enter the BSCB program and how it fits with your career goals. Completed applications should be submitted to Dr. Amy Burkert in Doherty Hall 1320.
Computational Biology is concerned with solving biological and biomedical problems using mathematical and computational methods.
Computational Biology is recognized as an essential element in modern biological and biomedical research. There have been fundamental changes in biology and medicine, over the past decade, due to spectacular advances in biomedical imaging, genomics, and proteomics. The nature of these changes demands the application of novel theories and advanced computational tools to decipher the implications of these data, and to devise methods of controlling or modifying biological function. Consequently, Computational Biologists must be well trained and grounded in biology, mathematics, and computer science.
Genetics, Genomics, and Proteomics
Sequence analysis
Evolutionary tree inference
Network inference
Gene clustering
Biological Modeling and Simulation
Predicting responses of biological systems
Testing possible mechanisms of molecular action
Testing methods for genetic analysis
Performing hypothetical experiments
Structural Biology
Protein folding and dynamics
Structure prediction
Structure assignment
Structure design
Biological Image Analysis
Interpreting physiological data
Disease state detection
Automated instrument reading
Automated interpretation of microscopy data
Computational Neuroscience
Genetic basis of neural function
Computing with neurons
Neural representation of information