Bioinformatics, MS

The Master of Science (MS) in Bioinformatics seeks to provide students with core knowledge in bioinformatics programming, integrating knowledge from the biological, computational, and mathematical disciplines. Upon completion, students are equipped to apply bioinformatics and computational methods to biological problems. Students in the MS program have the opportunity to gain professional work experience via an optional co-op. 

The program consists of core course work in computational methods, programming, and statistics, enhanced by electives in molecular biology, biochemistry, molecular modeling, web development, database design and management, data mining, and other related topics.

Complete all courses and requirements listed below unless otherwise indicated.

Core Requirements

Computational Methods
BINF 6308Bioinformatics Computational Methods 14
BINF 6309Bioinformatics Computational Methods 24
Research and Seminar
BIOL 6381Ethics in Biological Research2
BINF 7385Bioinformatics Seminar2
Statistics and Programming
BINF 6200Bioinformatics Programming4
MATH 7340Statistics for Bioinformatics4

Electives

Complete 12 semester hours from the following. Electives outside this list may be chosen in consultation with faculty advisor. 12
Medical Physiology
Biomedical Imaging
Cellular Engineering
Biology Colloquium
Plant Biotechnology
Stem Cells and Regeneration
Microbial Biotechnology
Advanced Microbiology
Medical Microbiology
Biological Imaging
Immunology
Evolution
Comparative Neurobiology
Advanced Genomics
Cell and Molecular Biology of Aging
Immunotherapies of Cancer and Infectious Disease
Molecular Cell Biology for Biotechnology
Biochemistry
Molecular Cell Biology
Neurobiology and Behavior
Dynamics of Microbial Ecology
Biochemistry for Molecular Biologists
Introduction to Biotechnology
Basic Biotechnology Lab Skills
The Biotechnology Enterprise
Managing and Leading a Biotechnology Company
Biotechnology Entrepreneurship
Economics and Marketing for Biotechnology Managers
Bioprocess Fundamentals
Cell Culture Processes for Biopharmaceutical Production
Downstream Processes for Biopharmaceutical Production
Drug Product Processes for Biopharmaceuticals
Molecular Interactions of Proteins in Biopharmaceutical Formulations
Cutting-Edge Applications in Molecular Biotechnology
Higher-Order Structure Analytics
Biotechnology Applications Laboratory
Introduction to Glycobiology and Glycoprotein Analysis
Protein Mass Spectrometry
Protein Mass Spectrometry Laboratory
Protein Chemistry
Molecular Modeling
Analytical Biochemistry
Analytical Biotechnology
Programming Design Paradigm
Foundations of Artificial Intelligence
Database Management Systems
Principles of Programming Language
Managing Software Development
Computer Systems
Web Development
Fundamentals of Computer Networking
Algorithms
Machine Learning
Information Retrieval
Data Mining Techniques
Collecting, Storing, and Retrieving Data
Introduction to Data Mining/Machine Learning
Ecological Dynamics
and Lab for EEMB 5130
Introduction to Mathematical Methods and Modeling
Numerical Analysis 1
Numerical Analysis 2
Graph Theory
Probability 1
Probability 2
Mathematical Statistics
Regression, ANOVA, and Design
Nonparametric Methods in Statistics
Experimental Design and Biostatistics
Complex Networks and Applications
Network Science Data
Network Science Data 2
Introduction to Computational Statistics
Information Design and Visual Analytics

Program Credit/GPA Requirements

32 total semester hours required
Minimum 3.000 GPA required