About
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 needed to pursue a career in this dynamic field.
The MS in Bioinformatics is designed for working adults, but can be completed full-time. All classes are offered in the evening, on Saturdays, or online. Please note that not every course is available at all on-site locations. The degree can be completed online.
Visit the official programme website for more information.Study Mode: On Campus
Study Load: Full Time
Course Category: Medicine & Health
Degree Level: Master
Location: null,
Baltimore,
Maryland,
null,
usa.
Code | Title | Credits |
---|---|---|
Core Courses - Required: | ||
AS.410.602 | Molecular Biology | 4 |
AS.410.610 | Epigenetics, Gene Organization & Expression | 4 |
Core Courses - Customizable | ||
AS.410.633 | Introduction to Bioinformatics | 4 |
or EN.605.652 | Biological Databases and Database Tools | |
AS.410.634 | Practical Computer Concepts for Bioinformatics | 4 |
or EN.605.641 | Principles of Database Systems | |
EN.605.620 | Algorithms for Bioinformatics | 3 |
or EN.605.621 | Foundations of Algorithms | |
Select four of the following: | 16 | |
Bioinformatics: Tools for Genome Analysis | ||
Protein Bioinformatics | ||
Molecular Phylogenetic Techniques | ||
Next Generation DNA Sequencing and Analysis | ||
Gene Expression Data Analysis and Visualization | ||
Bioperl | ||
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: | 3 | |
Foundations of Software Engineering | ||
XML Design Paradigms | ||
Introduction to Machine Learning | ||
Data Visualization | ||
Principles of Enterprise Web Development | ||
Agile Development with Ruby on Rails | ||
Mobile Application Development for the Android Platform | ||
Software Systems Engineering | ||
Large-Scale Database Systems | ||
Advanced Machine Learning | ||
Evolutionary Computation | ||
Independent Project in Bioinformatics | ||
Big Data Processing Using Hadoop | ||
Biotechnology | ||
Select one of the following: | 4 | |
Advanced Cell Biology I | ||
Advanced Cell Biology II | ||
Human Molecular Genetics | ||
Principles of Immunology | ||
Microbiology | ||
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 |
Visit the official programme website for more information.
Visit the official programme website for more information.
Visit the official programme website for more information.
Visit the official programme website for more information.
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