Bioinformatics, M.S.

Program Director: Daniel Sierra-Sosa, Ph.D., [e-mail], 301-696-3724

Bioinformatics is a multidisciplinary field that combines biology, computer science, and mathematics to develop methods for the processing and interpretation of biological data. Bioinformatics drives biological research through the development of computational tools while computational biology focuses on the use of existing tools to analyze and interpret biological data. The M.S. in Bioinformatics is designed to ensure that students develop expertise in both the biological and computational concepts needed for success as either a bioinformatician or as a computational biologist. Employers are seeking bioinformaticians and computational biologists with a strong understanding of the underlying biology and the ability to analyze and interpret complex data. Students will learn to perform robust and reproducible analyses using existing computational resources and will gain the skills necessary to build new computational tools adapted to evolving data types. In addition, students will develop the leadership and communication skills necessary to function effectively in a complex matrix environment. Students are encouraged to showcase their skills through internships or collaborative projects, and the degree culminates in a hands-on capstone or thesis experience that can be performed at a wide variety of nearby federal and corporate biotech labs.

The MS in Bioinformatics has the following learning outcomes:

a) Demonstrate proficiency in R, Python, Unix/Linux and an understanding of programming best practices. 

b) Obtain, utilize, archive, and share data using the best practices for reproducible research.

c) Understand, interpret and present results from “–omics” data, including Next Generation Sequencing results.

d) Apply principles of machine learning to identify and interpret patterns in data.

e) Utilize leadership skills to plan and execute a project in a matrix environment.

Application Requirements:

Students wishing to enter the program must have 1) a completed undergraduate degree (BA or BSc) in a life science or computer science field with a GPA of 2.75 or higher; or 2) an in-progress or completed Hood College Certificate in Bioinformatics with a 3.0 or higher; or 3) a completed Master's degree (MA or MSc) in a biology-related field or computer science related field with a 3.0 or better.

Program Requirements

The 33-credit M.S. in Bioinformatics includes options for a 3-credit capstone project or a 6-credit thesis. All of the classes are taught in the evening by experts in the field who interact personally with their students. The degree includes a required “gateway” foundational course that differs according to the student’s background in either biology or computer science. The coursework includes the following:

Core Courses - 24 credits required

BIFX 501/BMS 501	Foundation in Life Sciences	3.0
	or
BIFX 502	Foundations in Computer Science	3.0
BIFX 503	Biostatistics in R	3.0
BIFX 504	Advanced Molecular Bio for Bioinformatics	3.0
BIFX 545	Leading Reproducible Research	3.0
BIFX 550	Functional Genomics: Sequence Analysis and Structural Bioinformatics	3.0
BIFX 551	Advanced Programming for Bioinformatics	3.0
BIFX 552	Bioinformatics Data Skills	3.0
BIFX 553	Applied Data Science for Bioinformatics	3.0

Elective Courses - 3-6 credits required

Students electing to pursue the Capstone path (BIFX 579), will complete two elective courses (6 credits). Students electing to pursue the thesis path (BIFX 580A and B), will complete one elective course (3 credits).

BIFX 546	Machine Learning for Bioinformatics	3.0
BIFX 547	Building and Using Web-based BIFX Applications	3.0
BIFX 548	Data Visualization for Bioinformatics	3.0
BIFX 572	Computational Genomics Practicum	3.0
BIFX 530/IT 530	Applied Database Systems	3.0

Capstone or Thesis

BIFX 579	Bioinformatics Capstone	3.0
	or
BIFX 580A	Bioinformatics Master's Thesis I	3.0
	and
BIFX 580B	Bioinformatics Master's Thesis II	3.0