Quantitative and Computational Biology (MS)

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The Department of Quantitative and Computational Biology offers a Master of Science in Quantitative and Computational Biology (QCB), which integrates quantitative graduate courses from the Biological Sciences, Biomedical Engineering, Chemistry, Computer Science, Mathematics, Physics and Astronomy, and Quantitative and Computational Biology departments. Students will gain additional skills across these disciplines that prepare them well for advanced graduate-level work, MD/PhD programs at top universities and/or jobs in industries at the intersection of biotechnology and software development.

The program requires 32 units, as indicated below.

Required Courses (8 units)

Students must complete the following courses.

QBIO 502 Molecular Biology for Quantitative Scientists Units: 4
QBIO 542 Seminar in Computational Biology Units: 1
QBIO 547 Ethics and Professional Conduct in Computational Biology Units: 1
QBIO 577 Computational Molecular Biology Laboratory Units: 2

Research Experience (7-9 units)

Students are required to enroll for 7 to 9 units of directed research in a laboratory approved by the department.

QBIO 590 Directed Research Units: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12

Foundational Elective Courses (8 units)

Select two of the following courses.

CSCI 455x Introduction to Programming Systems Design Units: 4
MATH 407 Probability Theory Units: 4
MATH 408 Mathematical Statistics Units: 4
QBIO 401 Introduction to Computational Analysis of Biological Data Units: 4
QBIO 475 Statistical and Evolutionary Genetics Units: 4
QBIO 478 Computational Genome Analysis Units: 4
QBIO 479L Computational Genome Analysis Laboratory Units: 4
QBIO 481 Structural Bioinformatics: From Atoms to Cells Units: 4
QBIO 482 Systems Biology: Modeling the Dynamics of Life Units: 4
QBIO 499 Special Topics Units: 1, 2, 3, 4, 5, 6, 7, 8
SCRM 487 Regenerative Medicine: Principles, Paradigms and Practice Units: 4

Graduate-Level Elective Courses (7-9 units)

Select two or three of the following courses. Options include 3- and 4-unit courses.

BISC 545 Modeling and Numerical Techniques for Marine Scientists Units: 2
BME 530 Introduction to Systems Biology Units: 4
CHEM 538 Mathematical Techniques of Physical Chemistry Units: 4
CHEM 540 Introduction to Statistical Mechanics Units: 4
CHEM 544 Introduction to Quantum Chemistry Units: 4
CSCI 561 Foundations of Artificial Intelligence Units: 4
CSCI 567 Machine Learning Units: 4
CSCI 570 Analysis of Algorithms Units: 4
CSCI 596 Scientific Computing and Visualization Units: 4
MATH 505a Applied Probability Units: 3
MATH 507a Theory of Probability Units: 3
MATH 541a Introduction to Mathematical Statistics Units: 3
MATH 541b Introduction to Mathematical Statistics Units: 3
PHYS 518 Thermodynamics and Statistical Mechanics Units: 3
PHYS 558a Quantum Mechanics Units: 3
PHYS 690 Introduction to Physical Biology Units: 3
QBIO 578a Computational Molecular Biology Units: 3
QBIO 578b Computational Molecular Biology Units: 3