Program in Quantitative and Computational Biology

Faculty

Program Information

The Program in Quantitative and Computational Biology is offered by the Lewis-Sigler Institute for Integrative Genomics and its affiliated departments. It is designed for students with a strong interest in big data and other quantitative approaches to biology. The curriculum introduces students to experimental techniques for acquisition of large-scale quantitative observations of biological systems, and the interpretation of such data in the context of appropriate models.

Examples of ongoing research include organizational principles of metabolic networks, quantitative modeling of cell biological processes, the genetic basis of complex behavior, comparative genomics of regulatory networks, quantitative analysis of gene-environment interactions, evolution of gene regulation, and circuitry driving aging.

At the core of the curriculum is independent research initiated in the fall of sophomore or junior year, in which students participate in the design, execution, and analysis of experiments in a host laboratory of their choice. The required courses provide a strong background in modern methodologies in data analysis, interpretation, and modeling. A certificate in quantitative and computational biology is awarded to students who successfully complete the program requirements.

Admission to the Program

Students are admitted to the program after they have chosen a concentration and consulted with the program committee, or the Director of the program, in May of their sophomore year. Although students are encouraged to find a lab on their own, the program committee will, if necessary, assist students in selecting a laboratory for their junior independent and senior thesis work. Students must have identified a lab and research project by the first day of their junior year fall semester. Admission requires the completion of prerequisites listed below. Electives are chosen in consultation with the adviser.

Prerequisites (which are to be completed by the end of the second year)
There are two possible tracks for entry into the QCB certificate program:

1. Integrated Science: ISC 231-234
                -OR-
2. All of the following courses:   
    •  COS 126 or higher
  •  MOL 214
  •  PHY 103-104 or PHY 103-108 or the equivalent by permission of the Director
  •  CHM 201-202 or CHM 337 or the equivalent by permission of the Director
  •  One 200-level math course (or higher) - OR - one semester of statistics: SML 201, ORF 245, MOL/EEB 355 or higher (but not PSY 251)


Please note that students can use their AP credits for the PHY and CHM requirements as per the university's Reference Table for AP Credit.

     •   AP 5 on Parts I and II of Physics C gives equivalency for PHY 103-104
     •   AP 4 on Chemistry gives equivalency for CHM 201 (but not CHM 202)
     •   AP 5 on Chemistry gives equivalency for CHM 201-202


Program of Study

For the Class of 2022 and beyond, the requirements for the certificate are as follows (Classes of 2020 and 2021 should consult the appropriate archived version of  the Undergraduate Announcement):

1. QCB 302: Research Topics in QCB (taken in the fall of sophomore or junior year)

2. CHM 301 / CHM 304: Organic Chemistry I: Biological Emphasis and Organic Chemistry II: Foundations of Chemical Reactivity and Synthesis 
           -OR-
    CHM 337: Organic Chemistry: Bioengineering Emphasis 

3. Junior and senior independent work must have significant overlap with areas in quantitative and computational biology.

4. Three electives from the course list below (Additional courses may be taken as electives with approval from the Director):

  • CBE 433 Mechanics/Dynamics of Soft Living Matter
  • CBE 440 The Physical Basis of Human Disease
  • CBE 447/GHP 447 Metabolic Engineering
  • CHM 440 Drug Discovery in the Genomics Era
  • CHM 541/QCB 541 Chemical Biology II
  • COS 343 Algorithms for Computational Biology
  • EEB 324 Theoretical Ecology
  • EEB 325 Mathematical Modeling in Biology and Medicine
  • ENV 302/EEB 302 Practical Models for Environmental Systems
  • GEO 523 / CEE 572 Geomicrobiology
  • ISC 326 Human Genomics: Past, Present, Future
  • MAE 344/MAE 566 Biomechanics and Biomaterials: From Cells to Organisms
  • MAT/APC 321 Numerical Methods
  • MAT 586/APC 511/MOL 511/QCB 513 Computational Methods in Cryo-Electron Microscopy
  • NEU 314 Mathematical Tools for Neuroscience
  • NEU 437 / MOL 437 / PSY 437 Computational Neuroscience
  • PHY 209 Computational Physics Seminar
  • PHY 412 Biological Physics
  • QCB 408/508 Foundations of Applied Statistics and Data Science (with Applications in Biology)
  • QCB 455/COS 551 Introduction to Genomics and Computational Molecular Biology
  • QCB 490 Molecular Mechanisms of Longevity: The Genetics, Genomics, and Cell Biology of Aging
  • QCB 505 Topics in Biophysics and Quantitative Biology: Statistical Mechanics for Real Biological Networks
  • QCB 511 Modeling Tools for Cell and Developmental Biology
  • QCB 515 Method and Logic in Quantitative Biology
     

Administrative Details

A minimum of a B average in program courses and junior and senior independent work is required for successful completion of the program. Program courses cannot be taken Pass/D/Fail.

Applications for program admission, including the Research Lab form, must be submitted by May 31 of sophomore year and should include the following information: prerequisite courses, plans for courses in the junior and senior years, and independent work plans. Admission decisions are made by June 30.

Certificate of Proficiency

Students who fulfill the requirements of the program receive a certificate of proficiency in quantitative and computational biology upon graduation. Students who pursue a certificate in quantitative and computational biology may not also receive a certificate in biophysics.

 

 

Courses

ISC 231 An Integrated, Quantitative Introduction to the Natural Sciences I (also
CHM 231
/
COS 231
/
MOL 231
/
PHY 231
) Fall STL

An integrated, mathematically and computationally sophisticated introduction to physics, chemistry, molecular biology, and computer science. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214 and COS 126. Students must enroll in ISC231 and ISC232 in the fall and ISC233 and ISC234 in the spring. Prerequisites: familiarity with calculus at the level of MAT103/104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session. Instructed by: T. Gregor, J. Akey, M. Wühr

ISC 232 An Integrated, Quantitative Introduction to the Natural Sciences I (also
CHM 232
/
COS 232
/
MOL 232
/
PHY 232
) Fall QR

An integrated, mathematically and computationally sophisticated introduction to physics, chemistry, molecular biology, and computer science. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214 and COS 126. Students must enroll in ISC 231 and ISC 232 in the fall and ISC 233 and ISC 234 in the spring. Prerequisites: familiarity with the calculus at the level of MAT 103-104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session. Instructed by: T. Gregor, J. Akey, M. Wühr

ISC 233 An Integrated, Quantitative Introduction to the Natural Sciences II (also
CHM 233
/
COS 233
/
MOL 233
/
PHY 233
) Spring STL

An integrated, mathematically and computationally sophisticated introduction to physics and chemistry, drawing on examples from biological systems. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214, and COS 126. Students must enroll in ISC 231 and ISC 232 in the fall and ISC 233 and ISC 234 in the spring. Prerequisites: familiarity with the calculus at the level of MAT 103-104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session. Instructed by: J. Shaevitz, O. Troyanskaya, M. Wühr

ISC 234 An Integrated, Quantitative Introduction to the Natural Sciences II (also
CHM 234
/
COS 234
/
MOL 234
/
PHY 234
) Spring

An integrated, mathematically and computationally sophisticated introduction to physics and chemistry, drawing on examples from biological systems. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214 and COS 126. Students must enroll in ISC 231 and ISC 232 in the fall and ISC 233 and ISC 234 in the spring. Prerequisites: familiarity with the calculus at the level of MAT 103-104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session. Instructed by: J. Shaevitz, O. Troyanskaya, M. Wühr

QCB 302 Research Topics in QCB Fall STN

This class is aimed at sophomores and juniors pursuing the QCB Certificate. Students choose a lab and engage in independent research by start of fall term. Course is centered on discussion, guidance, and feedback on student's own independent research. Students will learn to think critically about quantitative and computational experimental design, data analysis, and scientific communication. Students will present background research and progress reports. Written work includes an NSF-style research proposal and problem sets. Course culminates in a final symposium that is open to the public. Prerequisites: ISC231-234 or equivalent preparation. Instructed by: A. Amodeo, B. Adamson, S. Davidson

QCB 408 Foundations of Applied Statistics and Data Science (with Applications in Biology) Spring QR

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 will be extensively used to explore methods and analyze data. Instructed by: J. Storey

QCB 455 Introduction to Genomics and Computational Molecular Biology (also
MOL 455
/
COS 455
) Fall QR

Introduction to computational and genomic approaches used to study molecular systems. Topics include computational approaches to sequence similarity and alignment, phylogenetic inference, gene expression analysis, structure prediction, comparative genome analysis, and high-throughput technologies for mapping genetic networks. Two lectures, one preceptorial. Instructed by: J. Akey, M. Singh

QCB 490 Molecular Mechanisms of Longevity: The Genetics, Genomics, and Cell Biology of Aging (also
MOL 490
) Spring

Aging is a fascinating biological phenomenon because it seems inevitable, yet recent research suggests that longevity can be manipulated through genetics and environment. Moreover, aging is the major risk factor for a host of chronic and neurological diseases; thus, understanding the molecular regulation of aging will be critical in addressing these health issues in the future. We will explore the current state of the field, including genetic discoveries of longevity mutants, cell biological and metabolic characterization of aging animals, and genomic and computational analyses used to uncover molecular mechanisms that control longevity. Instructed by: C. Murphy