MS in Bioinformatics
Joint Offering with the Whiting School of Engineering
Johns Hopkins University offers an innovative graduate program that prepares professionals for success in bioinformatics. Drawing from the strengths of the Krieger School of Arts and Sciences and the Whiting School of Engineering, this program fully integrates the computer science, bioscience, and bioinformatics skills and knowledge needed to pursue a career in this dynamic field.
The 11-course degree program is thesis-optional and can be completed part-time or full-time and onsite, online, or through a combination of onsite and online courses.
Admissions Criteria for All Advanced Academic Programs
PROGRAM-SPECIFIC REQUIREMENTS
In addition to the materials and credentials required for all programs, the Master of Science in Bioinformatics requires an undergraduate degree in the biological sciences or engineering with at least a 3.0 on a 4.0 scale.
- Resume
- Statement of purpose: Please provide a statement, up to one page in length, describing your personal background and/or a part of your life experience that has shaped you or your goals. Feel free to elaborate on personal challenges and opportunities that have influenced your decision to pursue a graduate degree at Johns Hopkins.
- Program-specific prerequisite courses:
- Two semesters of organic chemistry
- One semester of biochemistry
- One semester of an introduction to programming using Java, C++, C, or Python
- One semester of data structures
- One semester of probability/statistics
- One semester of calculus
Program Requirements
Students in the MS in Bioinformatics program must complete 11 courses:
- Two required core courses
- Seven customizable core courses
- One elective from bioscience
- One elective from computer science
After completing the above courses, students may choose an independent study project (optional).
| Code | Title | Credits |
|---|---|---|
| Core Courses - Required: | 8 | |
| Molecular Biology | ||
| Epigenetics, Gene Organization & Expression | ||
| Core Courses - Customizable | 11 | |
| Introduction to Bioinformatics | ||
or EN.605.652 | Biological Databases and Database Tools | |
| Practical Computer Concepts for Bioinformatics | ||
or EN.605.641 | Principles of Database Systems | |
| Algorithms for Bioinformatics | ||
or EN.605.621 | Foundations of Algorithms | |
| Select four of the following: 1, 2, 3 | 16 | |
| Bioinformatics: Tools for Genome Analysis | ||
| Protein Bioinformatics | ||
| Molecular Phylogenetic Techniques | ||
| Next Generation DNA Sequencing and Analysis | ||
| Gene Expression Data Analysis and Visualization | ||
| Advanced Practical Computer Concepts for Bioinformatics | ||
| Advanced Genomics and Genetics Analyses | ||
| Practical Introduction to Metagenomics | ||
| Genomic and Personalized Medicine | ||
| Linked Data and the Semantic Web | ||
| Neural Networks | ||
| Principles of Bioinformatics | ||
| Computational Genomics | ||
| Computational Drug Discovery,Dev | ||
| Statistics for Bioinformatics | ||
| Modeling and Simulation of Complex Systems | ||
| Algorithms for Structural Bioinformatics | ||
| Systems Biology | ||
| Applied Machine Learning | ||
| Electives | ||
| Computer Science | ||
| Select one of the following: 1, 3 | 3 | |
| Foundations of Software Engineering | ||
| XML Design Paradigms | ||
| Principles and Methods in Machine Learning | ||
| Data Visualization | ||
| Principles of Enterprise Web Development | ||
| Mobile Application Development for the Android Platform | ||
| Software Systems Engineering | ||
| Large-Scale Database Systems | ||
| Advanced Machine Learning | ||
| Evolutionary and Swarm Intelligence | ||
| Independent Project in Bioinformatics | ||
| Big Data Processing Using Hadoop | ||
| Biotechnology | ||
| Select one of the following: 1, 2 | 4 | |
| Advanced Cell Biology | ||
| Cellular Signal Transduction | ||
| Human Molecular Genetics | ||
| Principles of Immunology | ||
| Virology | ||
| Molecular Basis of Pharmacology | ||
| Genes & Disease | ||
| Gene Therapy | ||
| Emerging Infectious Diseases | ||
| Cancer Biology | ||
| Clinical & Molecular Diagnostics | ||
| Clinical Trial Design and Conduct | ||
| Recombinant DNA Laboratory | ||
| High Throughput Screening & Automation Lab | ||
| Independent Research in Biotechnology | ||
| Total Credits | 42 | |
- 1
You may select other electives with the approval of your adviser
- 2
See course listings page for the Center for Biotechnology Education
- 3
MS in Bioinformatics with Thesis Option
Students interested in pursuing the MS in Bioinformatics with the thesis are required to take 12 courses. The thesis requires a two-semester research project. Students complete AS.410.800 Independent Research in Biotechnology first and AS.410.801 Biotechnology Thesis the following semester. Students interested in this option should consult with the program director or their academic adviser.
Learning Outcomes
Students in this program will:
- Critique current and classic research in molecular biology
- Search public databases in order to analyze data in a biological context
- Implement sequence alignment tools to elucidate the deeper context of biological data
- Develop bioinformatics tools to address biological problems
- Write computer programs to build databases within a biological context in multiple computer languages
- Design deployable computer algorithms
- Develop skills to meet individual career goals in computational biology and related fields.