Bioinformatics and Computational Biology, M.S.

The use of computational techniques and information systems has revolutionized research in the biological sciences — from the analysis of DNA sequences and the understanding of gene expression and regulation to the structural modeling of proteins and RNAs and the evolutionary relationship between species. The Master of Science in Bioinformatics and Computational Biology program brings together expertise from Saint Louis University in biology, chemistry, computer science, mathematics and statistics, biochemistry and molecular biology.


Maureen J. Donlin, Ph.D.
     Program Director

Curriculum Overview

The 30-credit bioinformatics and computational biology program is designed for students with academic backgrounds in the life sciences, mathematics, computer science, health sciences, engineering and statistics. The curriculum consists of a mix of required courses that build a strong foundation in bioinformatics and computational biology and elective classes that allow students to specialize in their expertise. Full-time students can complete the program in 18 to 24 months. Part-time students are welcome in the program.

Graduate Handbook

Fieldwork and Research Opportunities

Bioinformatics and computational biology program students must complete either a research experience with faculty or an internship with a biotech firm in the St. Louis area, which is home to one of the largest concentrations of biotech companies in the country. This requirement gives our M.S. students the opportunity for hands-on experience working with academic researchers or private industry. Industry partners include:

  • Bayer-Monsanto
  • BioSTL
  • Cofactor Genomics
  • Confluence Discovery Technologies
  • Donald Danforth Plant Sciences Center
  • Mallinckrodt Pharmaceuticals
  • MoGene
  • Nestlé-Purina
  • PierianDx
  • Sigma-Aldrich


There are many employment opportunities for graduates with a Master of Science in Bioinformatics and Computational Biology in the biotechnology, pharmaceutical, health care and software industries, as well as in academic, private and governmental research labs. St. Louis is home to many large and small biotech firms and is a national leader in biotech startups. St. Louis has medical schools at Saint Louis University and Washington University and is home to the Donald Danforth Plant Sciences Center, a world leader in plant and life sciences.

Admission Requirements

A bachelor's degree in biology, biochemistry, computer science, engineering, health science, mathematics, statistics or a similar scientific field is required. The faculty admissions committee considers the applicant's prior coursework or experience in genetics, biology and computer programming when determining the required coursework.

Application Requirements

  • Application completion 
  • Transcript(s) 
  • One letter of recommendation is required; two more are optional 
  • Résumé 
  • Statement of professional goals 
  • GRE general test scores are optional

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Requirements for International Students

All admission policies and requirements for domestic students apply to international students. International students must also meet the following additional requirements:

  • Demonstrate English Language Proficiency
  • Financial documents are required to complete an application for admission and be reviewed for admission and merit scholarships. 
  • Proof of financial support that must include:
    • A letter of financial support from the person(s) or sponsoring agency funding the student's time at Saint Louis University
    • A letter from the sponsor's bank verifying that the funds are available and will be so for the duration of the student's study at the University
  • Academic records, in English translation, of students who have undertaken postsecondary studies outside the United States must include:
    • Courses taken and/or lectures attended
    • Practical laboratory work
    • The maximum and minimum grades attainable
    • The grades earned or the results of all end-of-term examinations
    • Any honors or degrees received.

WES and ECE transcripts are accepted.

Application Deadlines

  • April 15
  • March 15 is the priority deadline for scholarship award consideration.


Tuition Total Program Cost
MS Bioinformatics and Computational Biology $42,000

Additional charges may apply. Other resources are listed below:

Net Price Calculator

Information on Tuition and Fees

Miscellaneous Fees

Information on Summer Tuition

Scholarships, Assistantships and Financial Aid

Scholarships are available to both U.S. and international students. Research assistantships are offered to select students working on faculty research projects. 

For priority consideration for scholarship awards and graduate assistantships, applicants should complete their applications by the program admission deadlines.

For information about financial aid, visit the Office of Student Financial Services at

  1. Graduates will be able to design and implement in silico experiments for biological problems.
  2. Graduates will be able to apply and combine existing tools for processing and analysis of biological data sets.
  3. Graduates will be able to use small- and large-scale quantitative data sets to model complex biological systems.
  4. Graduates will be able to work as part of multidisciplinary teams in corporate or academic environments.
  5. Graduates will be able to effectively communicate research approaches and findings.
Required Courses
BCB 5200Introduction Bioinformatics I3
BCB 5250Introduction Bioinformatics II3
BCB 5300Algorithms in Computational Biology3
BCB 5810Bioinformatics Colloquium1
BIOL 5030Genomics3
Biology Elective3-4
Select one of the following:
Biochemical Pharmacology
Advanced Molecular Biology
Molecular Phylogenetic Analysis
Computer Science Elective3
Select one of the following:
Concurrent and Parallel Programming
Distributed Computing
Introduction to Machine Learning
Internship/Research Experience1-3
Select one of the following:
Bioinformatics Internship
Research Topics
Research Topics
Research Topics
Research Topics
Bioinformatics & Computational Biology Electives7-10
Select remaining courses to reach 30 credits:
Courses may also be selected from Biology and Computer Science Electives listed above.
Molecular Techniques Lab
Advanced Biological Chemistry
Advanced Cell Biology
Geographic Information Systems in Biology
Advanced Principles of Virology
Concepts of Immunobiology
Advanced Microbiology
Medical Imaging
Brain Computer Interface
Principles of Software Development
Software Engineering
Web Technologies
Evolutionary Computation
Introduction to Artificial Intelligence
Deep Learning
Computer Vision
Biochemistry 1
Biochemistry 2
Computational Chemistry
Principles of Medicinal Chemistry
Biophysical Chemistry
Analytics and Statistical Programming
Predictive Modeling and Machine Learning
Introduction to Analysis
Multivariable Analysis
Probability Theory
Time Series
Mathematical Statistics
Applied Regression
Bayesian Statistics and Statistical Computing
Total Credits30

Continuation Standards

Students must maintain a cumulative grade point average (GPA) of 3.00 in all graduate/professional courses.

Prerequisite Courses

The following course may be required to fill in missing prerequisite coursework, such as data structures. These prerequisite courses do not count toward the 30 credits needed for graduation.

Students may complete these prerequisites as part of the program, but the courses will not count toward the 30 credits required for the degree.

Roadmaps are recommended semester-by-semester plans of study for programs and assume full-time enrollment unless otherwise noted.  

Courses and milestones designated as critical (marked with !) must be completed in the semester listed to ensure a timely graduation. Transfer credit may change the roadmap.

This roadmap should not be used in the place of regular academic advising appointments. All students are encouraged to meet with their advisor/mentor each semester. Requirements, course availability and sequencing are subject to change.

Plan of Study Grid
Year One
Critical course:   Participation in BCB Colloquium  
Critical course:  BCB 5200 Introduction Bioinformatics I 3
Critical course:  BIOL 5030 Genomics 3
Critical course:  BCB 5250 Introduction Bioinformatics II 3
BIOL 5090 Biometry 4
CSCI 5570 Machine Learning for Networks 3
BCB 5910 Bioinformatics Internship 1
Year Two
Critical course:  BCB 5300 Algorithms in Computational Biology 3
BCB 5810 Bioinformatics Colloquium 1
BIOL 5700 Advanced Molecular Biology 3
CSCI 5300 Software Engineering 3
CSCI 5610 Concurrent and Parallel Programming 3
 Total Credits30

Apply Now

For questions about the program or application process, please contact:

Maureen J. Donlin, Ph.D.
Program Director

Graduate Admission