Graduate Education in Computational Biology & Bioinformatics

Students interested in graduate thesis research in the CCBM should apply to the Department of Biomedical Engineering Master of Science in Engineering Program or the Doctoral Program in Biomedical Engineering . Students may also do graduate research in the CCBM while enrolled in the graduate programs of the departments of Electrical and Computer Engineering , Applied Mathematics and Statistics and Computer Science .

The following is the Biomedical Engineering PhD Program Curriculum in Computational Biology & Bioinformatics

Undergraduate Prerequisites:

Students should have sufficient undergraduate preparation in mathematics, physics, chemistry and computer science. Courses in calculus, differential equations, linear algebra, object-oriented programming languages, general physics and general chemistry are assumed. Courses in real and complex analysis, partial differential equations, probability theory are recommended.

Life Sciences:

Two life sciences tracks have been defined. One is based on the first year SOM basic sciences curriculum. The second is based on the Biochemistry, Cell and Molecular Biology core curriculum of the SOM  Basic Science Departments. We encourage our students to take the latter.

Year 1 Medical School Life Sciences Track

1 st year Medical School basic sciences curriculum

Year 1 Alternate Life Sciences Tracks

Biochemistry, Cell and Molecular Biology (BCMB) Core

1. 800.600 Molecules and Cells

2. 260.709 Molecular Biology and Genomics

3. 260.708 Genetics

4. 340.703 Cell Structure and Dynamics

5. 360.728 Pathways and regulation

6. 800.708 BCMB Core Discussion

7. Undergraduate/graduate level coursework and/or lab rotation as may be arranged in the Spring Semester

and/or elect from the following

1. 020.380 Molecular Biology

2. 020.633 Developmental Genetics

3. 020.638 Regulation and Mechanisms of Cell Cycle

4. 020.634 Chromatin & Transcription

5. 360.720 Physiology

Engineering and Physical Sciences

The following curriculum is to be completed in Year 2 if taking the SOM basic life sciences track or in Years 1-2 if taking the alternative BCMB. Students are required to take at least 2 courses per semester in Year 2, with at least one of these being at the 600/700 level. Curricula are to be designed with the guidance of the student's mentor. Electives are given below.

Recommended Core Course: Foundations of Computational Biology and Bioinformatics

This course provides the foundation for theoretical and computational studies of biological systems.  Topics include statistical mechanics of equilibrium and non-equilibrium systems, reaction kinetics, biological networks, biomechanics, molecular simulations, reactive diffusion and transport, statistical analysis of DNA and protein sequences, pattern recognition, machine learning, database systems, and high-performance computing.  Students will be expected to build computational implementations of the algorithms discussed. Advanced mathematical concepts will be introduced as required.

Mathematics/Engineering

Assumed Undergraduate Prerequisites

Calculus, ordinary differential equations, linear algebra, probability theory (at a level equivalent to 550.420 Introduction to Probability Theory), real/complex analysis (at a level equivalent to 110.405 Analysis 1 and 110.311 Methods of Complex Analysis)

Electives

1. 550.437 Statistics, Information and Vision

2. 550.435 Bioinformatics and Statistical Genetics

3. 550.620 Probability Theory I

4. 550.621 Probability Theory II

5. 550.630 Statistical Theory

6. 550.631 Statistical Inference

7. 550.632 Multivariate Statistical Inference

8. 550.692 Matrix Analysis and Linear Algebra

9. 550.471 Combinatorial Analysis

10. 550.391 Dynamical Systems

11. 550.491 Applied Analysis for Engineers and Scientists

12. 520.447 Introduction to Information Theory and Coding

13. 520.621 Nonlinear System Theory

14. 520.601 Introduction to Linear Dynamical Systems

15. 110.607 Complex Variables

16. 530.730 Finite Element Methods

17. 530.766 Introduction to Numerical Methods

18. 530.639 Scientific Computing

19. 530.661 Applied Mathematics for Engineering

20. 530.761-762 Mathematical Methods of Engineering

21. 530.766 Numerical Methods

22. 530.659 Applied Analysis for Engineers and Scientists

23. 540.651 Advanced Transport Phenomena

Computer Science

Assumed Undergraduate Prerequisites

C/C ++ , Java. Recommended courses include data structures (at a level equivalent to 600.226 Data Structures) and algorithms (at a level equivalent to 600.363 Introduction to Algorithms)

Quantitative Biology (All Research Tracks)

Electives

1. 520.636 Feedback Control in Biological Signaling Pathways

2. 520.610 Computational Functional Genomics

3. 580.690 Systems Biology of Cell Regulation

4. 580.682 Computational Models of the Cardiac Myocyte

5. 540.409 Modeling Dynamics and Control for Chemical and Biological Systems

6. 580.639 Models of Neuron

7. 140.638 Analysis of Biological Sequences

8. 140.688 Statistics for Gene Expression

Electives (Bioinformatics Research Track)

1. 600.475 Machine Learning

2. 600.415 Database Systems

3. 600.774 Kernel Machine Learning

Cell Engineering Electives (Systems Biology Track)

1. 520.495 Microfabrication lab

2. 580.441 Cellular Engineering

3. 580.451 Cellular Engineering Lab

4. 570.411 Engineering Microbiology

5. 540.410/640 Chemical Engineering for Micro and Nanotechnology

6. 540.431 Biochemical Engineering/Biotechnology

Bioethics Elective

1. 306.655 Ethical Issues in Public Health