MS in Bioinformatics

The emphasis of the MS program is preparation for mid-level industrial positions in bioinformatics, and the MS degree constitutes a “Pre-professional MS.” Credits earned in the MS program may be applicable to the PhD program, but the MS program is not intended to be a stepping-stone toward a PhD. (MS candidates wishing to enter the PhD program must apply for admission to that program via the normal application process.)

The master’s degree requires 32 credits of coursework, with at least 20 chosen from the program’s core. In order to receive a master’s degree, students must demonstrate mastery of the core subject matter (no lower than a B in all core courses). They must also demonstrate a working knowledge of computational methods available to the modern bioinformatician by completing an internship as part of their degree requirements. Upon completion of the internship, the student is required to submit a written report on the internship experience. This report serves in lieu of an MS thesis. A brief written report from the intern’s supervisor is also required. Internship credit is obtained by registering for ENG BF 541, Bioinformatics Internship, or ENG BF 501/502, Bioinformatics Master’s Project. The required credit hours may vary.

Required Core Courses (20+ cr total)

  • CAS BI 552* Molecular Biology I (4 cr)
  • ENG BE 562** Computational Biology: Genomes, Networks, Evolution (4 cr)
  • ENG BE 768 Biological Database Systems (4 cr)
  • ENG BF 541 Bioinformatics Internship (variable cr)
  • ENG BF 778 Physical Chemistry for Systems Biology (4 cr)
  • ENG BF 821 Bioinformatics Graduate Seminar (2 cr each; 4 cr total)

*Students may take CAS BI 553, Molecular Biology II, if approved by their advisor.
**Students with no prior experience or exposure to bioinformatics application should take ENG BF 527, Bioinformatics Applications, before taking ENG BE 562.

Fulfillment of core course equivalents will be determined based on documented previous academic and/or work experience. The student and his or her advisor will petition the curriculum committee for such equivalencies. When either past work or an alternate course has been accepted as a core equivalent, the student’s advisor will recommend other courses to fulfill the 20 core credit hours. Advanced elective courses should be taken in place of any waived course requirements.

The remaining credits needed to complete the requirements for the MS degree will consist of electives and/or additional research projects.

Suggested Curriculum:

First Year:

  1. CAS BI 552 Molecular Biology I (4 cr)
  2. ENG BE 562 Computational Biology: Genomes, Networks, Evolution (4 cr)
  1. ENG BF 778 Physical Chemistry for Systems Biology (4 cr)
  2. ENG BE 768 Biological Database Systems (4 cr)
  3. ENG BF 821 Bioinformatics Graduate Student Seminar (2 cr each semester)

SUMMER: Students may begin the internship

Second Year:

  1. ENG BF 821 Bioinformatics Graduate Student Seminar (2 cr)
  2. ENG BE 562 Computational Biology: Genomes, Networks, Evolution (4 cr) if not taken in first year
  1. ENG BE 777 Computational Genomics (4 cr)
  1. ENG BF 541 Bioinformatics Internship, or ENG BF 501/502 Bioinformatics Master’s Project

Background enhancement: Typically students enrolling in the Bioinformatics MS Program have strength in either the computational area or in biochemistry/molecular biology, but not both. In consultation with their academic advisor, they may decide to take or audit some introductory courses to strengthen areas where their background has deficiencies. Examples of such courses (which do not carry graduate credit) are:

  • CAS BI 203 Cell Biology
  • CAS BI 206 Genetics
  • CAS CH 172 Principles of Organic and Biochemistry
  • CAS CH 273 Principles of Biochemistry
  • CAS CS 112 Introduction to Computer Science II
  • CAS MA 213 Basic Statistics and Probability

Breadth Electives

  • CAS BB 522 Molecular Biology Laboratory
  • CAS BI 502 Topics in the Theory of Biological Networks
  • CAS BI 504 Advanced Evolutionary Analysis
  • CAS BI 549 Molecular Phylogenetics and Evolution
  • CAS BI 553 Molecular Biology II
  • CAS BI 556 Membrane Biochemistry and Cell Signaling
  • CAS BI 560 Systems Biology
  • CAS BI 572 Advanced Genetics
  • CAS BI/CH 527/528 Biochemistry Laboratory I & II
  • CAS CH 525 Physical Biochemistry
  • CAS CS 542 Machine Learning
  • CAS CS 549 Pattern Matching and Detection with Applications in Biological Sequence Analysis
  • CAS CS 565 Data Mining
  • CAS MA 555 Numerical Analysis I
  • CAS MA 565 Mathematical Models in the Life Sciences
  • CAS MA 575 Linear Models
  • CAS MA 576 Generalized Linear Models
  • CAS MA 581 Probability
  • CAS MA 582 Mathematical Statistics
  • CAS MA 583 Introduction to Stochastic Processes
  • CAS MA 584 Multivariate Statistical Analysis
  • CAS MA 614 Statistical Methods II
  • CAS MA 684 Applied Multiple Regression and Multivariable Methods
  • ENG BE 560 Biomolecular Architecture
  • ENG BE 565 Molecular Biotechnology
  • ENG BE 566 DNA Structure and Function
  • ENG BE 569 Next Generation Sequencing
  • ENG BE 764 Biophysics of Large Molecules
  • ENG BF 527 Applications in Bioinformatics
  • ENG BF 571 Dynamics and Evolution of Biological Networks
  • ENG EC 533 Advanced Discrete Mathematics
  • ENG EC 534 Discrete Stochastic Methods
  • ENG EC 730 Information-Theoretical Design of Algorithms
  • GMS PA 600 Introduction to Pathology & Pathophysiology of Disease
  • GRS BI 610 Developmental Biology
  • GRS BI 735 Advanced Cell Biology
  • GRS BI 755 Cellular and Systems Neuroscience
  • GRS CH 751 Advanced Topics in Physical Chemistry
  • GRS CH 752 Advanced Topics and Chemical Physics
  • GRS MA 770 Mathematical and Statistical Methods of Bioinformatics
  • GRS MA 881 Statistics Seminar I
  • GRS MA 882 Statistics Seminar II
  • GRS MB 721 Graduate-Level Biochemistry
  • GRS MB 722 Advanced Biochemistry
  • GRS PY 771 Systems Biology for Physical Scientists and Engineers
  • SPH BS 704 Introduction to Biostatistics
  • SPH BS 830 Design and Analysis of Microarray Experiments and Next Generation Sequencing
  • SPH BS 855 Bayesian Modeling for Biomedical Research & Public Health
  • SPH BS 858 Statistical Genetics I
  • SPH BS 859 Applied Genetic Analysis
  • SPH BS 860 Statistical Genetics II

Internship Guidelines

Internships provide the bridge between classroom/laboratory study and “real-world” employment. Each student must complete an internship with a minimum of 400 hours of on-the-job experience (e.g., 10 weeks full-time work in the summer). The format is very flexible, and part-time internships running concurrently with classes or employment are acceptable. Students whose regular, full-time job includes a strong bioinformatics component over at least a 6-month period can request that this be considered an internship. Students must consult with their academic advisor to assess the suitability of a proposed internship. For this purpose, “bioinformatics” means extensive use of computational tools to analyze, display and/or archive biological information (usually at the molecular level). The project supervisor must be familiar with the tools employed, and if possible, the position should involve regular interaction with “wet-bench” scientists. While most internships will take place in industrial settings, suitable projects can be completed in nonprofit or academic research laboratories. In every case the student must obtain final approval from the Program Director before commencing an internship. For full-time students the internship should begin no later than the third semester after beginning the MS program.

Academic Advising

The Associate Director of Graduate Studies serves as the student’s primary academic advisor. Students should consult with the director to tailor their coursework to meet specific curricular needs in the transition into an interdisciplinary program. The director will also be available to advise them with regard to internship placements that will satisfy degree requirements.