Program of Study

Program of Study

Course requirements are tailored individually based on the student’s background and interests to ensure that they have a solid and rigorous computational biology foundation.

As an interdisciplinary program, CBM has implemented a focused, but flexible curriculum and requires students to obtain knowledge of fundamental principles in biology, computational science, and mathematics to ensure competency within these disciplines.

COURSEWORK

Students must complete at least 4 courses in year 1. If you are interested in taking a course that is not listed below, please contact CBM Associate Director, Dr. Ekta Khurana for approval.

CBM Required Coursework

Course Code Credits Course Name Campus
TPCM 5001.01 0.5 credits CBM Seminar and Journal Club I Weill Cornell
TPCM 5004.01 0.5 credits CBM Seminar and Journal Club II Weill Cornell
PBSB 5006.04 1 credit Critical Dissection of Scientific Data (spring) Weill Cornell
RCRP 9010.01 1 credit Tri-Institutional Responsible Conduct of Research (RCR) Weill Cornell

Additional Requirements

Dates Research Seminar Requirements
Years 2-5 CBM Annual RCR Case-Study Refresher (2-hour workshop)
All Years CBM Student Research in Progress Seminar Series
All Years CBM Annual Symposium

Approved Core-Level Coursework

Course Code Credits Course Name Campus
CMPB 5001 01 4 credits Dynamic Models in Biology Weill Cornell
CMPB 5002 01 4 credits Data Structures & Algorithms for Computational Biology Weill Cornell
CMPB 5005 03 4 credits Functional Interpretation of High-Throughput Data Weill Cornell
BTRY 4830/6830 3 credits Quantitative Genomics and Genetics
(crosslisted at WCM as PBSB 5021)
Cornell-Ithaca
ECE 5412 3 credits Bayesian Estimation and Stochastic Optimization
(crosslisted at WCM as TPCB 9001 01)
Cornell-Ithaca
CS 5785 3 credits Applied Machine Learning Cornell Tech

Approved Electives


Weill Cornell Medicine
Course Code Credits Course Name     Institution
CMPB 5004 03 4 credits Analysis of Next Generation Sequencing Data Weill Cornell
NUER 5013 03 1.5 credits Mathematical Structures in Neuroscience Weill Cornell
CMPB 5003 01 4 credits Cellular and Molecular Biology Weill Cornell
PBSB 5019 04 0.5 credits Clinical and Research Genomics Weill Cornell
NEUR 5003.01
NEUR 5003.03
1.5 credits
1.5 credits
From Neuron to the Brain I
From Neuron to the Brain II
Weill Cornell
IAMP 5001
IAMP 5002
5.5 credits
4.5 credits
Fundamental Immunology I
Fundamental Immunology II
Weill Cornell
TPCM 5003.01 3 credits Genomic Innovation
(via the New York Genome Center)
Weill Cornell
BCMB 5009 01 1.5 credits Stem Cell Biology Weill Cornell
Rockefeller University

For more information about RU classes, please download the course catalog (pdf file).

Course Code Credits Course Name     Campus
RU 1 credit Mathematical Modeling Rockefeller
RU 5.5 credits Cell Biology Rockefeller
RU 1.5 credits Development of CNS Circuits Rockefeller
RU 2 credits Microbial Pathogenesis Rockefeller
RU 2.5 credits Molecular Basis of Cancer Rockefeller
RU 2.5 credits Stem Cells in Tissue Morphogenesis and Cancer Rockefeller
Cornell-Ithaca
Course Code Credits Course Name     Host
ORIE 6500 4 credits Applied Stochastic Processes Cornell-Ithaca
ORIE 6741 3 credits Bayesian Machine Learning Cornell-Ithaca
BTRY 6381 3 credits Biomedical Data Mining and Modeling
(crosslisted at WCM as PBSB 9202 01)
Cornell-Ithaca
BTRY 6840 4 credits Computational Genetics and Genomics
(crosslisted at WCM as PBSB 9203 01)
Cornell-Ithaca
BTRY 6520 4 credits Computational Intensive Statistical Methods Cornell-Ithaca
STSCI 4740 4 credits Data Mining and Machine Learning Cornell-Ithaca
CS 4320 3 credits Introduction to Database Systems Cornell-Ithaca
CS 6785 3 credits Deep Probabilistic and Generative Model
(crosslisted at WCM as PBSB 9211 03)
Cornell-Ithaca
BTRY 4030 3 credits Linear Models with Matrices Cornell-Ithaca
CS 5780 3 credits Introduction to Machine Learning Cornell-Ithaca
CS 5786 3 credits Machine Learning for Data Science Cornell-Ithaca
CS 6210 3 credits Matrix Computation Cornell-Ithaca
CS 4210 3 credits Numerical Analysis and Differential Equations Cornell-Ithaca
BTRY 6820 3 credits Statistical Genomics: Coalescent Theory and Human Population Genomics Cornell-Ithaca
BTRY 6010
BTRY 6020
4 credits
4 credits
Statistical Methods I
Statistical Methods II
Cornell-Ithaca
ORIE/STSCI 7170 3 credits Theory of Linear Models Cornell-Ithaca
BIOMG 6330 2 credits Biosynthesis of Macromolecules Cornell-Ithaca
BIOMG 4880 3 credits Cancer Genetics
(crosslisted at WCM as PBSB 9210 03)
Cornell-Ithaca
VETMM 6100 2 credits Cellular and Molecular Pharmacology Cornell-Ithaca
PSYCH 6140 4 credits Computational Psychology Cornell-Ithaca
BIOMG 4870 3 credits Human Genomics
(crosslisted at WCM as PBSB 9204 01
Cornell-Ithaca
BIOMG 4390 3 credits Molecular Basis of Disease
(crosslisted at WCM as PBSB 9209 03)
Cornell-Ithaca
BIOMG 6390 2 credits The Nucleus Cornell-Ithaca
BIOMG 4810 4 credits Population Genetics
(crosslisted at WCM as PBSB 9201 11
Cornell-Ithaca
BME 6120 3 credits Precision and Genomic Medicine Cornell-Ithaca
BIOMG 6310 3 credits Protein Structure and Function Cornell-Ithaca
BIOMG 4380 3 credits RNA in Biology and Medicine Cornell-Ithaca
Cornell Tech
Course Code Credits Course Name     Institution
CS 5112 3 credits Algorithms and Data Structures for Applications Cornell Tech
CS 5304 3 credits Data Science in the Wild Cornell Tech
CS 5787 3 credits Deep Learning Cornell Tech
ECE 5242 3 credits Intelligent Autonomous Systems Cornell Tech
CS 5670 4 credits Introduction to Computer Vision Cornell Tech
CS 5740 3 credits Natural Language Processing Cornell Tech
CS 5854 3 credits Networks and Markets Cornell Tech
ECE 5411 3 credits Statistical Signal Processing and Reinforcement Learning Cornell Tech
CS 5435 3 credits Security and Privacy Concepts in the Wild Cornell Tech
CS 6741 3 credits Topics in Natural Language Processing and Machine Learning Cornell Tech

THESIS YEARS

If a student selects a thesis mentor at Weill Cornell or Sloan Kettering, they join the Weill Cornell Graduate School, a partnership with Sloan Kettering Institute; if thesis research is to be conducted at The Rockefeller University, student joins the David Rockefeller Graduate Program in Bioscience.  When a student selects a thesis mentor in Cornell Ithaca, they are affiliated with the Computational Biology Field.  Regardless of where the student is based, all are considered trainees in the CBM program.

Admissions to Candidacy Exam (NYC and Ithaca)

Deadline: June 30 of 2nd year
NYC-based students will write and defend a thesis proposal for their Admission to Candidacy Examination (ACE); Ithaca-based students will complete their A Exam. These exams must be successfully completed and registered according to the guidelines of the graduate school in which the student is matriculated. Originals of all required forms must be filed with the appropriate graduate school, and duplicates must be filed with the CBM office.

Thesis Committee Meetings

Thesis Committee meetings are required at least every 9 months in Years 3 and 4, then at least every 6 months in Year 5 and beyond; thesis committee reports must be filed with CBM and the graduate school in which the student is enrolled.

LAB ROTATIONS

Prior to choosing a thesis laboratory, students complete research rotations with faculty of their choosing. These rotations provide the student the opportunity to experience a range of thesis research options and thereby enable an informed thesis laboratory decision.

Students must complete at least 3 rotations (in Ithaca and/or NYC) in their first 12 months in the program (beginning in July). Dates may be modified after consultation with CBM Co-Directors.

Find out more in the Timeline.

PROGRAM SYMPOSIUM

A student-organized retreat is held off-site every summer to bring together students from the three institutions. The 2-day event features a keynote speaker (selected and invited by students), alumni panel, oral presentations and a poster session. Student and faculty sessions are scheduled to discuss any changes to program structure and other suggestions to improve the overall training experience. In addition, the event provides students with time for recreational activities and other social events.

Previous Symposiums

2020

Location: Virtual Symposium
Keynote Speaker: Dr. Gad A. Getz, Director, Cancer Genome Computational Analysis and Institute Member, Broad Institute

2019

Location: Crystal Springs Resort, Hamburg, NJ
Keynote Speaker: Dr. Tal Nawy, Senior Program Manager, Dana Pe’er Lab, MSK
CBM Alumni Speakers: Dr. Julie Yang and Dr. Lauren Fairchild

2018

Location: Mohonk Mountain House, New Paltz, NY
Keynote Speaker: Dr. Tuuli Lappalainen, Columbia University, New York Genome Center
CBM Alumni Speakers: Dr. Kaitlyn Gayvert and Dr. Kelson Zawack

2017

Location: Mohonk Mountain House, New Paltz, NY
Keynote Speaker: Dr. Sam Globus, Director of Scientific Operations, Celmatix
CBM Alumni Speakers: Dr. Nyasha Chambwe and Dr. Byron Roberts
Job Search Panel (CBM recent graduates): Dr. Neel Madhukar and Dr. Priyanka Vijay