Bioinformatics Program (M.S.)
Gain the skills and knowledge necessary to excel in this growing field. Learn current best practices for processing big, biological data in a small, supportive environment. Build your own applications for new problems and design pipelines with existing tools for rapid, automated discovery research.
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Program Overview
M.S. in Bioinformatics (30 Credits)
For professionals in all STEM disciplines including biology, environmental science, computer science, and health professions, this graduate program will train you to analyze complex biological data sets from genomics and proteomics experiments. You will learn foundational principles in computer science, statistics, and biology to solve complex, multifaceted problems in biology.
- Curriculum covers computer programming, data acquisition and mining, research methods, and statistical analysis.
- Collaborative learning environment with opportunities to enhance skills in critical thinking, problem solving, conceptualization of solutions, study design, and communication with biological and computer scientists.
- Laboratory workshops in genomics and proteomics
- Personal advising
- Networking opportunities and job placement support
- Yellow Ribbon/Military Friendly
- No GRE required
- $1,133/credit tuition. Program can be completed in less than a year.
Now enrolling for a May 2024 start!
Learning OutcomesUpon completion of the program, students will demonstrate:
- an ability to apply knowledge of computing, biology, statistics, and mathematics appropriate to the discipline
- an ability to analyze a problem, and identify and define the computing requirements appropriate to its solution
- an ability to use current techniques, skills, and tools necessary for bioinformatics practice
- an understanding of professional, ethical, legal, security and social issues and responsibilities
- an ability to communicate effectively with a range of audiences
Required Core Courses (18 credits)
BIN 501 - Introduction to Programming for Bioinformatics (3 cr)BIN 510 - Probability and Statistics with Programming (3 cr)BIN 520/520L - Molecular Genetics and Lab (3 cr)BIN 521/521L - Protein Biochemistry and Lab (3 cr)BIN 601 - Advanced Programming for Bioinformatics (3 cr)BIN 602 - Data Mining for Bioinformatics (3 cr)Elective Courses (12 credits)
Students must complete twelve credits from the list below:
BIN 603 - Principles of Software Design and Engineering (3 cr)BIN 610 - Advanced Statistics and Data Visualization (3 cr)BIN 620 - Biological Sequence Analysis (3 cr)BIN 621 - Cheminformatics and Drug Discovery (3 cr)BIN 650 - High-Throughput Screening and Image Analysis (3 cr)BIN 651 - Biological Systems Analysis (3 cr)BIN 670 - Introduction to Machine Learning and Distributed Computing (3 cr)BIN 680 - Bioinformatics Internship (6 cr)ORBIN 690 - Bioinformatics Thesis (6 cr)Total Degree Requirements - 30 credits
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Curriculum
Curriculum Requirements - Total Credits Required: 30
Required Curriculum - 18 Credits
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BIN 501聽-聽Introduction to Programming for Bioinformatics (Cr: 3)
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BIN 510聽-聽Probability and Statistics with Programming (Cr: 3)
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BIN 520/520L聽-聽Molecular Genetics and Lab (Cr: 3)
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BIN 521/521L聽-聽Protein Biochemistry and Lab (Cr: 3)
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BIN 601聽-聽Advanced Programming for Bioinformatics (Cr: 3)
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BIN 602聽-聽Data Mining for Bioinformatics (Cr: 3)
Elective - 12 Credits
Students may select either BIN680 or BIN690 but not both
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BIN 603聽-聽Principles of Software Design and Engineering (Cr: 3)
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BIN 610聽-聽Advanced Statistics and Data Visualization (Cr: 3)
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BIN 620聽-聽Biological Sequence Analysis (Cr: 3)
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BIN 621聽-聽Cheminformatics and Drug Discovery (Cr: 3)
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BIN 622聽-聽Proteomics (Cr: 3)
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BIN 650聽-聽High-Throughput Screening and Image Analysis (Cr: 3)
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BIN 651聽-聽Biological Systems Analysis (Cr: 3)
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BIN 670聽-聽Introduction to Machine Learning and Distributed Computing (Cr: 3)
*Student may select BIN 680 or BIN 690 but not both
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BIN 680聽-聽Bioinformatics Internship (Cr: 6)
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BIN 690聽-聽Bioinformatics Thesis (Cr: 6)
Program Goals and Objectives
- To provide students with a broad understanding of the disciplines that comprise bioinformatics (biology, chemistry, computer science, mathematics, statistics) and the diverse functions of bioinformatics scientists.
- To provide students with in-depth knowledge of relevant biological sub-disciplines.
- To provide students with technical skills in computer programming, data acquisition and mining, research methods, and statistical analysis.
- To provide students with opportunities to enhance skills in critical thinking, problem solving, conceptualization of solutions, study design, and communication with biological and computer scientists.
- To provide students with an interdisciplinary and applied learning environment that integrates theory and real-world application.
Learning Outcomes
At the end of the program, the student will demonstrate:鈥�
- an ability to apply knowledge of computing, biology, statistics, and mathematics appropriate to the discipline
- an ability to analyze a problem, and identify and define the computing requirements appropriate to its solution
- an ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs in scientific environments
- an ability to use current techniques, skills, and tools necessary for bioinformatics practice
- an ability to function effectively on teams to accomplish a common goal
- an understanding of professional, ethical, legal, security and social issues and responsibilities
- an ability to communicate effectively with a range of audiences
- detailed understanding of the scientific discovery process and of the role of bioinformatics in it
- an ability to apply statistical research methods in the contexts of molecular biology, genomics, medical, and population genetics research
- in-depth knowledge of relevant areas of biology and an understanding of biological data generation techniques
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BIN 501聽-聽Introduction to Programming for Bioinformatics (Cr: 3)