Computational Biology

Computational Biology as a science is in the midst of a major transition, as modern experimental methods are generating data at an unprecedented rate. The availability of this data is leading to the development of quantitatively detailed models of complex biological systems and associated computational approaches to the study of biology.

The Stony Brook Department of Applied Mathematics and Statistics houses a strong research program in Computational Biology. Our faculty's interests span the full range of biological problems: genomic analysis and data-mining, computational structural biology, structure-based drug design, signaling and gene-regulatory networks, and cell and tissue models. For more information on computational biology research projects, see Computational Biology projects.  Further, Applied Math faculty and graduate students collaborate with faculty and graduate students in biomedical science departments to offer a rich multi-disciplinary training in computational biology. For example, lab rotations for Applied Math computational biology students involve faculty labs across the University and at nearby Cold Spring Harbor Laboratory.

A number of Stony Brook interdisciplinary biological initiatives foster close interactions between computational and experimental scientists. Among these are the Institute of Chemical Biology and Drug Discovery, the Centers for Molecular Medicine and programs at nearly Brookhaven National Laboratory (which is managed by Stony Brook).

Masters and Doctoral Program Requirements in the Computational Biology Track The standard professional degree in computational biology and biomedical sciences is a Ph.D. The computational biology track also offers a M.S. degree, consisting of 30 credits of graduate coursework with no thesis. The core courses required for the M.S. degree in computational biology are also taken by all PhD students in this track in preparation for the PhD qualifying examinations. For more details about requirements for the Ph.D., please see Ph.D. Requirements.

Course Requirements

The required courses provide computational biology students with the fundamentals of both biology and applied mathematics, as well as in specific methods and applications in computational biology. It is expected that the student will choose a set of electives to provide in depth specialization. Students with less formal training in either math or biology may wish to audit an undergraduate course concurrently with, or prior to, taking the graduate level courses. We refer to the Graduate Bulletin for further information about university and department-wide requirements.

Core Courses
Fundamentals of Applied Math
AMS 507 Introduction to Probability
AMS 510 Analytical Methods for Applied Mathematics and Statistics
AMS 533 Numerical Methods and Algorithms in Computational Biology

Fundamentals of Biology
CHE 541/MCB 520 Graduate Biochemistry (an alternate graduate level cell or developmental biology course may be substituted with permission)

Methods of Computational Biology 
AMS 531 Laboratory Rotations in Computational Biology (2 semesters) 
AMS 532 Journal Club in Computational Biology (3 semesters)
AMS 535 Introduction to Computational Structural Biology and Drug Design
AMS 537 Biological Networks and Dynamics
CSE 549 Computational Biology

Electives
AMS 530 Principles in Parallel Computing
AMS 534 Introduction to Systems Biology
AMS 536 Molecular Modeling of Biological Molecules
AMS 538 Methods in Neuronal Modeling 
CHE 538 Statistical Mechanics
CHE 533 Chemical Thermodynamics
PHY 558 Physical and Quantitative Biology 

Electives may also be chosen from any area relevant to computational biology, based on the specific interests of the student. The student is encouraged to consult with a faculty adviser in advance of choosing electives. Likely areas of specialization may include:

- Computational applied math
- Optimization and simulation of complex systems
- Structural biology/biochemistry
- Developmental/cell biology
- Biostatistics 

Qualifying Examinations

As with the other tracks in the department, the qualifying exam for the doctoral program consists of two parts: the Common Exam taken early in the spring semester of the first year, and the Area Exam taken a year later. Both cover the material from the core course sequence.

Common Exam

The common exam is a written exam, consisting of two parts. Part A of the exam covers the fundamentals of Linear Algebra and Advanced Calculus, as covered in AMS 510; all doctoral students in AMS take this portion of the exam. Part B of the exam is specific to Computational Biology, and consists of questions covering the basics of Computational Structural Biology (AMS 535) and Bioinformatics (CSE 549).

Area Exam

The area exam in computational biology is an oral exam based on the student's specific course sequence. The student is examined by a panel of at least three faculty and must answer questions from those courses the student has covered in each of these three key areas: fundamentals of applied mathematics; fundamentals of biology and/or biochemistry; methods and applications in computational biology as well as in the particular elective courses the student has taken. The oral format is chosen to allow greater flexibility in dealing with a range of students having different focus areas and in assessing the student's understanding of biological systems. Students should consult with the examination committee well prior to the exam in order to determine which areas/courses will be emphasized.

Suggested Course Sequence for the Computational Biology Track 

For a student entering in the fall semester, the following outline provides a suggested sequence through the first four semseters of the track.

SEMESTER 1 - Fall

1. AMS-510 (3 credits), Analytical Methods for Applied Mathematics and Statistics
2. CSE-549 (3 credits), Computational Biology
3. AMS-535 (3 credits), Intro to Computational Structural Biology & Drug Design (R. Rizzo)
4. Elective (3 credits)
5. AMS-531 (0/3 credits), Lab Rotations
6. AMS-532 (0/1 credits), Journal Club
7. AMS-539 (0/1 credits) Intro to Physical & Quantitative Biology

*** Please note that many students enroll in AMS 599 (Research) to fill their elective credits, and international students may be required to enroll in an ESL course. Both these options fulfill the need to maintain a full-time course load, but may not be counted towards the 30 graduate credits required for the MS degree.

COMMON EXAM (Ph.D. Students; first week of Spring semester)

• Part A (Linear Algebra) 3 of 4 written questions based on AMS-510
• Part A (Calculus) 3 of 4 written questions based on AMS-510
• Part B (Comp. Bio.) 3 of 4 written questions based on AMS-535 and CSE-549
• Make-up exam is held at end of the semester

SEMESTER 2 - Spring

1. AMS-533 (3 credits), Numerical Methods and Algorithms in Computational Biology (D. Green)
2. AMS-537 (3 credits), Biological Networks and Dynamics (T. MacCarthy)
3. Elective (3 credits)
4. Elective (3 credits)
5. AMS-531 (0/3 credits), Lab Rotations
6. AMS-532 (0/1 credits), Journal Club (includes Responsible Conduct of Research)
7. PHY-561 (1/3 credits) Introduction to Biology for Physical and Quantitative Scientists

SEMESTER 3 - Fall

1. AMS-507 (3 credits), Introduction to Probability
2. CHE-541/MCB-520 (3 credits), Graduate Biochemistry
3. Elective (3 credits)
4. AMS 532 (0/1 credits), Journal Club

*** Suggested elective PHY 558 Physical Biology

QUALIFYING AREA EXAM (Ph.D. Students; first week of Spring semester)

• An oral exam consisting of questions based on the graduate courses the student has taken that are not covered by the common exam.

SEMESTER 4 - Spring

1. AMS 699 Research
2. Elective
3. Elective
4. JRN 565 (3 credits) Communicating Your Science

*** For PhD students, the courses here should consist of 3 to 9 credits of thesis research augmented by elective courses. For MS students, 9 credits of elective courses should be taken.