Further information about the program

Admission Requirements
The candidates for admission to the program are expected to be graduates of Bioinformatics, Computer Science, Mathematics, Statistics, Science, Health, Engineering, Business, and Education with a GPA of at least 3.0. Students admitted to the program are required to take and pass recommended courses to remedy any deficiency in a discipline that serves as a foundation for the study of bioinformatics.

Application Process

The preferred qualification for admission to the MS Bioinformatics Program is a bachelor's degree in bioinformatics, biology, medical technology, chemistry, computer science, mathematics, statistics, and physics. Applicants with a bachelor's degree in engineering, business, and education related discipline would also be considered for admission.

Applicants should:
- Download the file Application Form from MSU's web site: www.morgan.edu/academics/downloads/default.asp
- Complete the Application Form.
- Submit the Application Form to:

School of Graduate Studies
Admission and Programs Office
Holmes Hall 206

For additional information on admission, tuition, financial aid, and application please:
- Visit the School of Graduate Studies web site: www.morgan.edu/academics or
- Contact the School of Graduate Studies Admission and Programs Officer at (443) 885-3185.

Faculty involved in the MS Bioinformatics Program:

  1. Computer Science (Eric Sakk, Vojislav Stojkovic, Samir Tannouri, Grace Steele, and William Lupton)
  2. Math (Asamoah Nkwanta, Earl Barnes, Ahlam Tannouri, Edward Danial)
  3. Biology (James Wachira, Viji Sitther, Ernest Steele, and Gerald Rameau)
  4. School of Engineering (Reginald Amory, James Whitney, and Ashraf Ahmed)
  5. School of Business and Management (Sanjay Bapna)


  1. Dr. Clay Breshears, Intel Corporation, Urbana-Champaign, Illinois
  2. Dr. Hongwei Huo, Xidian University, Xi'an, China
  3. Dr. Walter Schmidt, Environmental Microbial and Food Safety Laboratory, Beltsville, MD

What is Bioinformatics?

Bioinformatics is research, development, and/or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.

Computational Biology is development and/or application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.

Bioinformatics and computational biology involve the use of techniques from computer science, informatics, mathematics, and statistics to solve biological problems. Research in computational biology often overlaps with systems biology. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution.

The terms bioinformatics and computational biology are often used interchangeably. However bioinformatics more properly refers to the creation and advancement of algorithms, computational and statistical techniques, and theory to solve formal and practical problems posed by or inspired from the management and analysis of biological data. Computational biology, on the other hand, refers to hypothesis-driven investigation of a specific biological problem using computers, carried out with experimental and simulated data, with the primary goal of discovery and the advancement of biological knowledge. Computational biology also includes lesser known but equally important sub disciplines such as computational biochemistry and computational biophysics. A common thread in projects in bioinformatics and computational biology is the use of mathematical tools to extract useful information from noisy data produced by high-throughput biological techniques such as genomics. A representative problem in bioinformatics is the assembly of high-quality DNA sequences from fragmentary "shotgun" DNA sequencing, while in computational biology, a representative problem might be statistical testing of a hypothesis of common gene regulation using data from mRNA microarrays or mass spectrometry.

Why a Career in Bioinformatics?

Bioinformatics is an exciting and challenging new scientific discipline that has emerged from integration of the life sciences with the special fields of biology, medical technology, chemistry, physics, mathematics, statistics, computer science, artificial intelligence, and information technology. There is a tremendous demand for individuals with graduate degrees in bioinformatics because of the information being produced by the genome sequencing projects and the need to harness this for medical diagnostic, therapeutic uses, and other bio industrial applications.
Bioinformatics Research

Bioinformatics, computational biology, computer science, informatics, mathematics and statistics researchers at Morgan State University discover and implement mostly parallel algorithms:
- that facilitate the understanding of biological processes
- related to bio and computer security and information assurance through the application of artificial-computational intelligence, visualization, and statistical techniques.

MS Bioinformatics Program Objectives

Master of Science Bioinformatics Program is a multidisciplinary program administrated by the Computer Science Department within the School of Computer, Mathematical and Natural Sciences, which also houses the Departments of Biology, Chemistry, Mathematics, and Physics.
Program involves the required courses from Bioinformatics, Computer Science, Mathematics, and Statistics and the elective courses from Bioinformatics, Computer Science, Mathematics, Statistics, Science, Health, Engineering, or Business. This relatively new and rapidly expanding discipline integrates computer, mathematical, statistical, biological, chemical, physical, and etc. methods to solve problems in bioinformatics.

The Objectives of the Bioinformatics Program are:
- to provide students the theoretical foundations and practical skills in Bioinformatics.
- to prepare students for careers in bioinformatics/computational biology within industry, academia and government organizations.

The Bioinformatics Program is designed:
- to offer students the broad-based interdisciplinary research training necessary for professional work in industry and continued post-graduate training in the field.
- for working adults. All classes are offered in the evening or on weekends.

One of the major strengths of the Bioinformatics Program is its diversity in the range of research conducted by faculty, and diversity in the academic and cultural backgrounds of students.

Master of Science Bioinformatics Program is one of the best on the East Coast for:
- computing with Big Files
- parallel and distributing computing
- computing with cells and atoms (DNA and quantum computing)
- modeling, simulation, visualization, and animation of biological processes.

Graduates of the Master of Science Bioinformatics Program will have the educational foundation necessary to interpret complex biological information, perform analysis of sequence data using sophisticated bioinformatics software, and program software when needed.

If you are a hardworking, ambitious, smart person, with aspirations for leadership in a field that will change society, our Master of Science in Bioinformatics Program is what you are looking for.

Bioinformatics Computing Laboratory

Bioinformatics Computing Laboratory, Science Complex, Calloway Hall, Room 212

  1. 8 PCs
  2. 2 Macs 
  3. 1 Little Fe Cluster computer

connected in a network.

Each computer has installed the specific computing platform.
Windows XP, Windows 7, Linux, and Mac Operating Systems are available.
The lab has a variety of software for:
- Bioinformatics
- Quantum Computing
- DNA Computing
- Compiler Design
- Modeling and Simulation
- Visualization

The lab has a great collection of programming languages such as C, C++, Java, C#, Visual Basic, Microsoft Visual Programming Language, F#, Haskell, Cat, Easel, 3APL, Lisp, Prolog, Mathematica, Maple, Perl, and etc.

LittleFe is a 6 node Beowulf style portable mini-cluster computer which supports shared memory, distributed memory, GPGPU, and other parallelisms. It weighs less than 50 pounds, easily travels in a suitcase, and sets-up in 5 minutes. LittleFe is ideal for classroom demonstrations of Parallel and Distributed Computing. Dr. Stojkovic and MS Bioinformatics Program students use LittleFe with OpenMP, MPI, Cuda, and other Parallel and Distributed Computing platforms and programming models to study and research Parallel and Distributed Computing and solve challenging Bioinformatics problems.

Dr. Vojislav Stojkovic and MS Bioinformatics Program Students are one of very few Academic Community Member Participants selected to participate as recipients of the EAPF/SC11 LittleFe grant.