Computational Genomics Education and Training
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There are several ways to collaborate and learn at Johns Hopkins:
- Training Opportunities for graduate students
- JHU/JHMI Courses
Ph.D. Programs
Students interested in Ph.D. studies at Hopkins in genomics, computational biology, and related topics have a number of choices. While we do not have a Ph.D. program specifically in Bioinformatics or Genomics, our faculty supervise Ph.D. research in both these areas through a number of different graduate programs. Links to these programs can be found below, and potential students are encouraged to apply to the Ph.D. program that best matches their interests.
Students with a background in mathematics or statistics should consider applying to the Ph.D. program in Biostatistics at the Bloomberg School of Public Health. Biostatistics is ranked number 3 in the country and is an outstanding program overall, with multiple faculty members working in genomics.
Students with a background in computer science, mathematics, physics, or other statistics may consider applying to the Ph.D. program in Computer Science in the Whiting School of Engineering.
Students with training in engineering, biology, or computer science may consider the Ph.D. program in Biomedical Engineering (Joint program with Homewood and School of Medicine), ranked #1 in the country for many years.
- If your background is primarily in biology, consider the Ph.D. program in Human Genetics at the Institute of Genetic Medicine, School of Medicine, one of the premier human genetics programs in the world.
Summer Internships throught the Johns Hopkins Center for Computational Biology
The internship program will provide you with hands-on
research experience as part of ongoing research projects
with bioinformatics and genomics faculty in the
Institute of Genetic Medicine. Current areas of research include
analysis of high-throughput sequencing data to determine markers
of disease, characterize genes and their variations in species
such as human and mouse, reconstruct gene networks, and assemble
and analyze genomes. The program involves full-time research
for 8-12 weeks between May and August.
The program is open to undergraduates (including following their
senior year), as well as exceptional high-school students. You
do not need to be a Johns Hopkins University student to apply,
and applications from students at other universities are encouraged. For more information please go to the internship page on the Johns Hopkins Center for Computational Biology website.
JHU/JHMI Courses
| Term | Title | Course Number | Instructor |
| 1st | Perl For Bioinformatics | SPH 140.636.01 | Fernando Pineda |
| 1st | Statistical Computing | SPH 140.776.01 | Roger D. Peng |
| 1st | Computer Science for Bioinformatics | SPH 140.636.01 | Fernando Pineda |
| 1st | Statistics and Data Analysis Using R | ME:510.707 | Leslie Cope, Elana Fertig, Luigi Marchionni, and Robert Scharpf |
| 1st | Selected Topics in Computational Genomics | EN.601.850 | Benjamin Langmead |
| Frontiers of Sequencing Data Analysis | EN.601.750 | Benjamin Langmead |
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| Fall | Computational Genomics: Sequences | 601.447 / 601.647 | Benjamin Langmead |
| Spring | Introduction to Computational Genetics | ME:710.737 | Dan Eytan Arking |
| Fall | Advanced Topics in Genomic Data Analysis | EN.601.751 | Alexis Battle |
| Spring | Computational Genomics: Data Analysis | EN.601.448 | Alexis Battle |
| Fall | Advanced Topics in Genomic Data Analysis | EN.601.751 | Alexis Battle |
| 2nd | Analysis of Biological Sequences | SPH 140.638 | Sarah Wheelan |
| Computational Biology and Bioinformatics | ME:800.707 | Sarah Wheelan | |
| Spring | Computational Genomics Methods | ME:800.723 | Sarah Wheelan |
| 3rd & 4th quarters | Statistics for Laboratory Scientists I & II | SPH 140.615 SPH 140.616 |
Ingo Ruczinski |
| 4th term | Statistics for Genomics | SPH 140.688 | Jeff Leek |
| Computational Personal Genomics | EN.580.689 | Steven Salzberg | |
| 4th Term | Statistics for Genomics | SPH 140.688.01 | Ni Zhao |
| Spring | Introduction to Genomic Research | JHU 601.350 | Steven Salzberg |
| 1st Term | Statistical Computing | SPH 140.776.01 | Kasper Daniel Hansen |
| 1st Term | Methods in Biostatistics I | SPH 140.651 | |
| 1st Term | Methods in Biostatistics II | SPH 140.652 | |
| Fall | Introduction to Public Health and Biomedical Informatics | ME:600.903 | Harold P. Lehmann |
| Fall | Computational Biology and Bioinformatics | ME.800.707 (21870) | |
| Fall | Intro Algorithms | EN.601.633 | M. Dinitz |
| Spring | Computational Genomics: Applied Comparative Genomics | JHU 601.749 | Michael Schatz |
| Spring | Compilers & Interpreters | JHU 601.328 | Peter Froehlich |
| Fall | Statistical Machine Learning | EN.601.775 (Homewood) | R. Arora |
| Spring | Foundations of Computational Biology and Bioinformatics II | JHU 601.488 / EN.580.688 | Rachel Karchin |
| Fall | Selected Topics in Programming Languages | EN.601.826 | S. Smith |
| Spring | Fundamentals of Genome Informatics | AS.020.355 | James Taylor |
| Fall | Randomized and Big Data Algorithms | EN.601.634 | V. Braverman |
| Genomes and Development | 020.637 | ||
| Fall | Computational Genomics | EN.600.639 | |
| Fall | Practical Bioinformatics | NIH FAES BIOF 429 | |
| Fall | Bioinformatics for analysis of data generated by Next Generation Sequencing | NIH FAES BIOF 521 | |
| Fall | Computational Biology | NIH FAES BIOF 537 | |
| Fall | Computational Genomics | EN.600.639 |