Quantitative and Computational Biology

Academic Year: 
2019-20
Address: 
Carl Icahn Laboratory, Lewis-Sigler Institute for Integrative Genomics
Phone: 
609-258-9407
Website: 
Department of Quantitative and Computational Biology
Program offerings: 
Ph.D.
Director of Graduate Studies
John Storey
Graduate Program Administrator
Jennifer Brick

Overview

The Program in Quantitative and Computational Biology (QCB) is intended to facilitate graduate education at Princeton at the interface of biology, the more quantitative sciences, and computation. Administered from The Lewis-Sigler Institute for Integrative Genomics, QCB is a collaboration in multidisciplinary graduate education among faculty in the Institute and the Departments of Chemistry, Chemical and Biological Engineering, Computer Science, Ecology and Evolutionary Biology, Molecular Biology, and Physics. The program covers the fields of genomics, computational biology, systems biology, biophysics, quantitative genetics, molecular evolution, and microbial interactions.

Program Highlights

An Outstanding Tradition:  Chartered in 1746, Princeton University has long been considered among the world’s most outstanding institutions of higher education, with particular strength in mathematics and the quantitative sciences. Building upon the legacies of greats such as Compton, Feynman, and Einstein, Princeton established the Lewis-Sigler Institute of Integrative Genomics in 1999 to carry this tradition of quantitative science into the realm of biology.

World Class Research: The Lewis-Sigler Institute and the QCB program focus on attacking problems of great fundamental significance using a mixture of theory and experimentation. To maximize the chances of paradigm shifting advances, there is an emphasis on studying fundamental processes in biology, such as transcription and metabolism, in tractable model organisms including bacteria, yeasts, worms, and fruit flies.

World Class Faculty: The research efforts are led by the QCB program’s 40+ faculty, who include a Nobel Laureate, 8 members of the National Academy of Sciences, 4 Howard Hughes Investigators, and over a dozen early career faculty who have received major national research awards (e.g., NSF CAREER or NIH Innovator).

Personalized Education: A hallmark of any Princeton education is personal attention. The QCB program is no exception. Lab sizes are generally modest, typically 6 – 16 researchers, and all students have extensive direct contact with their faculty mentors. Many students choose to work at the interface of two different labs, enabling them to build close intellectual relationships with multiple principal investigators.

Stimulating Environment: The physical heart of the QCB program is the Carl Icahn Laboratory, an architectural landmark located adjacent to physics, biology, chemistry, neuroscience, and mathematics on Princeton’s main campus. Students have access to a wealth of resources, both intellectual and tangible, such as world-leading capabilities in DNA sequencing, mass spectrometry, and microscopy. They also benefit from the friendly atmosphere of the program, which includes tea and cookies every afternoon. When not busy doing science, students can partake in an active campus social scene and world class arts and theater events on campus.

Applying

Application Deadline: 
December 1 - 11:59PM Eastern Standard Time
Program Length: 
5 years
Application Fee: 
$95
Application Requirements: 
Statement of Academic Purpose
Resume/Curriculum Vitae
Recommendation Letters
Transcripts
Fall Semester Grades
Required Tests
English Language Tests
GRE : 
General Test optional/not required

Ph.D.

Ph.D. Requirements: 
Courses:

Two courses, QCB 515 and COS/QCB 551, are required for all students, as is a Responsible Conduct in Research (RCR) course.  Three additional courses must be completed and can be chosen from the following list.  Course selections must include at least one course from the quantitative courses list and one course from the biological courses list.

Note: The full course of study must be reviewed and approved by the Director of Graduate Studies (DGS).

Quantitative Courses (must take at least one)

  • CHM 515 Biophysical Chemistry I
  • CHM/MOL 550 Contemporary Problems in Molecular Biophysics
  • COS 511 Theoretical Machine Learning
  • MOL 510 Introduction to Biological Dynamics
  • MOL 518 Quantitative Methods in Cell and Molecular Biology
  • MOL 536 Advanced Statistics for Biology
  • PHY 561/2 Biophysics
  • QCB 505 Topics in Biophysics and Quantitative Biology 
  • QCB 508 Foundations of Applied Statistics and Data Science (with Applications in Biology)
  • QCB/CBE 511 Modeling Tools for Cell and Developmental Biology

Biological Courses (must take at least one)

  • CHM/QCB 541 Chemical Biology II
  • EEB 504 Fundamental Concepts in Ecology, Evolution, and Behavior II
  • EEB 507 Recent Research in Population Biology
  • MOL 504 Cellular Biochemistry
  • MOL 505 Molecular Biology of Prokaryotes
  • MOL 506 Cell Biology and Development
  • MOL 516 Genetics of Eukaryotic Organisms
  • MOL 520 Advanced Topics in Prokaryotic and Eukaryotic Cell Biology
  • MOL 523 Molecular Basis of Cancer
  • MOL 545 Advanced Microbial Genetics
  • MOL 559 Viruses: Strategy & Tactics

Selected undergraduate courses of interest

(Note: these do not count towards course requirements)

  • APC 350 Introduction in Differential Equations
  • CBE 448 Introduction to Nonlinear Dynamics
  • COS 226 Algorithms and Data Structures
  • ORF/MAT 309/380 Probability and Stochastic Systems
  • ORF 406 Statistical Design of Experiments
  • QCB 302 Research Topics in QCB
Pre-Generals Requirement(s):

Research Colloquium: QCB Graduate Colloquium
QCB Graduate Colloquium is a research colloquium that has been developed for QCB graduate students, usually held on an afternoon during the fall and spring terms. Graduate students have the opportunity to present their research to peers. 

Rotations
All students are required to complete a minimum of three research rotations, with a maximum of four, to explore possible research advisers.

General Exam:

The general examination is usually taken in January of the second year, and consists of a 7 page written thesis proposal and one 3-hour oral session on the student’s thesis proposal.

Qualifying for the M.A.:

The Master of Arts (M.A.) degree is normally an incidental degree on the way to full Ph.D. candidacy and is earned after a student successfully passes the general examination.  It may also be awarded to students who, for various reasons, leave the Ph.D. program, provided the student has completed all coursework, pre-generals requirements, and the written portion of the general examination.

Teaching:

At least two semesters of teaching are required for all graduate students. Students will typically teach in the fall and spring terms of their third year. Teaching assignments are made by the Director of Graduate Studies, and students are notified of assignments in the summer of their second year.

Post-Generals Requirement(s):

Committee Meetings
Research progress is overseen by a thesis committee selected by the student after passing the general exam.

Dissertation and FPO:

The dissertation and final public oral exam (FPO) are required for all Ph.D. students.  All students must write and successfully defend their dissertation according to Graduate School rules and requirements. 

Faculty

Director

Joshua D. Rabinowitz

Executive Committee

Coleen T. Murphy
Joshua D. Rabinowitz
Joshua W. Shaevitz
Olga G. Troyanskaya
Eric F. Wieschaus

Courses

Permanent Courses

Courses listed below are graduate-level courses that have been approved by the program’s faculty as well as the Curriculum Subcommittee of the Faculty Committee on the Graduate School as permanent course offerings. Permanent courses may be offered by the department or program on an ongoing basis, depending on curricular needs, scheduling requirements, and student interest. Not listed below are undergraduate courses and one-time-only graduate courses, which may be found for a specific term through the Registrar’s website. Also not listed are graduate-level independent reading and research courses, which may be approved by the Graduate School for individual students.

CHM 541 Chemical Biology II (also
QCB 541
) A chemically and quantitatively rigorous treatment of metabolism and protein synthesis, with a focus on modern advances and techniques. Topics include metabolic pathways and their regulation; metabolite and flux measurement; mathematical modeling of metabolism; amino acid, peptide and protein chemistry; protein engineering and selected applications thereof.
COS 551 Introduction to Genomics and Computational Molecular Biology (also
MOL 551
/
QCB 551
) Introduction to basic computational and genomic methods for analysis of biological systems. Topics include: sequence similarity and alignment, phylogenic inference, gene recognition, gene expression analysis, transcriptional networks, structure prediction, functional genomics and proteomics. This is primarily a graduate-level course; interested undergraduates will require permission from instructors.
MAT 586 Computational Methods in Cryo-Electron Microscopy (also
APC 511
/
MOL 511
/
QCB 513
) This course focuses on computational methods in cryo-EM, including three-dimensional ab-initio modelling, structure refinement, resolving structural variability of heterogeneous populations, particle picking, model validation, and resolution determination. Special emphasis is given to methods that play a significant role in many other data science applications. These comprise of key elements of statistical inference, image processing, and linear and non-linear dimensionality reduction. The software packages RELION and ASPIRE are routinely used for class demonstration on both simulated and publicly available experimental datasets.
QCB 501 Topics in Ethics in Science Discussion and evaluation of the role professional researchers play in dealing with the reporting of research, responsible authorship, human and animal studies, misconduct and fraud in science, intellectual property, and professional conduct in scientific relationships. Participants are expected to read the materials and cases prior to each meeting. Successful completion is based on regular attendance and active participation in discussion. This half-term course is designed to satisfy federal funding agencies' requirements for training in the ethical practice of scientists. Required for graduate students and post-docs.
QCB 505 Topics in Biophysics and Quantitative Biology (also
PHY 555
) Analysis of recent work on quantitative, theoretically grounded approaches to the phenomena of life. Topics rotate from year to year, spanning all levels of biological organization, including (as examples) initial events in photosynthesis, early embryonic development, evolution of protein families, coding and computation in the brain, collective behavior in animal groups. Assumes knowledge of relevant physics and applicable mathematics at advanced undergraduate level, with tutorials on more advanced topics. Combination of lectures with student discussion of recent and classic papers.
QCB 508 Foundations of Statistical Genomics This course establishes a foundation in applied statistics and data science for those interested in pursuing data-driven research. The course may involve examples from any area of science, but it places a special emphasis on modern biological problems and data sets. Topics may include data wrangling, exploration and visualization, statistical programming, likelihood based inference, Bayesian inference, bootstrap, EM algorithm, regularization, statistical modeling, principal components analysis, multiple hypothesis testing, and causality. The statistical programming language R is extensively used to explore methods and analyze data.
QCB 511 Modeling Tools for Cell and Developmental Biology (also
CBE 511
) Using a number of real biological systems, course demonstrates how mathematical models of complex natural systems can organize large amounts of data, provide access to properties that are difficult or impossible to measure experimentally, and suggest new experimental tests of proposed regulatory mechanisms. Participants will demonstrate these ideas in the context of cell and developmental biology. For QCB program students, quantitatively inclined molecular biology students, and physics, chemistry and engineering students interested in quantitative biology. An extension of MOL 510.
QCB 515 Method and Logic in Quantitative Biology (also
PHY 570
/
EEB 517
/
CHM 517
/
MOL 515
) Close reading of published papers illustrating the principles, achievements and difficulties that lie at the interface of theory and experiment in biology. Two important papers, read in advance by all students, will be considered each week; emphasis will be on student discussion, not formal lectures. Topics include: cooperativity, robust adaptation, kinetic proofreading, sequence analysis, clustering, phylogenetics, analysis of fluctuations, maximum likelihood methods.
QCB 590 Extramural Research Internship in Quantitative and Computational Biology A summer term, full-time research internship at a host institution to perform scholarly research directly relevant to a student's thesis work. Research objectives are determined by the student's advisor in consultation with the outside host and QCB Director of Graduate Studies. An initial project proposal, monthly progress reports, and a final report are required. Enrollment is limited to QCB students who have successfully passed their general exams.