Computational Biology

The Computational Biology Track is intended for students who wish to develop working knowledge of computational techniques and their applications to biomedical research. Recent advances in high-throughput technologies, e.g., for DNA sequencing and for measuring RNA expression via DNA microarrays, are changing the nature of biomedical research. They empower fundamental new understandings of biological mechanisms with far reaching applications to biological and medical sciences. To fulfill this promise, new computational techniques are needed to analyze genome sequences, protein structures, metabolic and regulatory pathways, evolutionary patterns and the genetic basis of disease. The computational-biology track seeks to provide state of the art understanding of this concomitant growth of high-throughput experimental techniques, computational techniques to analyze their data, the resulting new understandings of biological mechanisms and their applications to pharmacological and medical practice (from diagnosis to drug design).


Students must complete a total of 30 points and must maintain at least 2.7 overall GPA in order to be eligible for the MS degree in Computer Science.

  1. Computational Biology track requires:
  2. Breadth courses
    – Required Track courses (6pts)
    – Track Electives (6pts)
    – General Electives (6pts)
  3. 2 required courses (6 points): COMS W4761 (Computational Genomics) and either COMS W4771 or SIEO W4150/STAT 4001.
  4. 6 elective points at the 6000-level, at least 3 of these 6000-level points must be selected from the list of Elective Track Courses.
  5. 6 credits of general elective graduate courses, at 4000 level or above; at least 3 of these points must be CS graduate courses.
  6. At least 3 elective points must be selected from courses in biological departments.
  7. Students, who waive track requirements using previous courses, may complete the 30 graduate credits by expanding their electives selected from (a) the list of required track courses; (b) the list of elective track courses; or (c) other graduate courses.

Please use the Degree Progress Checklist to keep track of your requirements.


Visit the breadth requirement page for more information.


Students are required to complete the following courses. Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead.

 Course ID
COMS W4761 Computational Genomics

Students are required to complete 1 of the following courses:

 Course ID
COMS W4771 or STAT 4400 Machine Learning or Statistical Machine Learning
SIEO W4150* Probability and Statistic

* STAT 4001 taken Spring 2018 or prior may count as a substitute for Probability and Statistics/Advanced Data Analysis


Students are required to take 2 courses from the following list, at least one of which must be a 6000-level course. Other courses on this list may be used as general electives or waiver replacements when the student has received a waiver.

 Course ID
COMS W4111 Introduction to Databases
COMS W4252 Introduction to Computational
Learning Theory
COMS W4772 (E6772) Advanced Machine Learning
COMS W4995 Visit the topics courses page to see which COMS 4995 courses apply to this track.
COMS E6111 Advanced Database Systems
COMS E6901 Projects in Computer Science (Advisor approval required)
COMS E6998 Visit the topics courses page to see which COMS 6998 courses apply to this track.
BIOC W4512 Molecular Biology
BIOL W4031 Genetics I
BIOL W4032 Genetics II
BIOL W4034 Biotechnology
BIOL W4037 Bioinformatics of Gene Expression
BIOL W4041 Cell Biology
BIOL W4070 The Biology and Physics of
Single Molecules
BIOL W4300 Drugs and Disease
BIOL W4073 Cellular and Molecular Immunology
BIOL W4400 Biological Networks
BIOL W4510 Genomics of Gene Regulation
BIOL G6560 Human Evolutionary Genetics
BCHM G4026 Biochemistry of Nucleic
and Protein Synthesis
BCHM G4250 Biochemistry and Molecular
BCHM G6300 Biochemistry and Molecular
Biology of Eukaryotes I
BCHM G6301 Biochemistry and Molecular
Biology of Eukaryotes II
BMEN E6480 Computational Neural Modeling
and Neuroengineering
GEND G4050 Advanced Eukaryotic
Molecular Genetics
STAT G6101 Statistical Modeling and Data Analysis
APMA E4400 Introduction to Biophysical Modeling
BINF G4006 Translational Bioinformatics
BINF G4014 Computational Biology I:
Functional and Integrative Genomics
BINF G4015 Computational Systems Biology:
Proteins, Networks, Function
BINF G4017 Deep Sequencing
ECBM E4060 Intro to Genomic Info Sci & Tech
EECS E6720 Bayesian models for Machine Learning
EECS E6894 Deep Learning for Computer Vision and Natural Language Processing


Students are required to complete at least 6 additional graduate points at, or above, the 4000 level; at least 3 of these points must be CS, the other 3 points may be a technical or non-CS/non-track elective approved by the track advisor. Please complete a non-track approval form, get your advisor’s approval, and forward it to CS Student Services. At most 3 points overall of the 30 graduate points required for the MS degree may be non-CS/non-track.

*Due to a significant overlap in course material, MS students not in the Machine Learning track can only take 1 of the following courses – COMS 4771, ELEN 4903, IEOR 4525, STAT 4240, STAT 4400/4241/5241 – as part of their degree requirements.


Please visit the Directory of Classes to get the updated course listings. Please also note that not all courses are offered every semester, or even every year. A few courses are offered only once every two or three years or even less frequently.


Please direct all questions concerning the Computational Biology Track to Prof. Itsik Pe’er.


Candidates preparing for graduation should submit a completed application for degree to the Registrar’s Office and submit a track graduation form/checklist to CS Student Services.
Last Updated: 4/21/16