The Ph.D. programs in Computational Biology at Johns Hopkins University span four Departments and a wide range of research topics. Our programs provide interdisciplinary training in computational and quantitative approaches to scientific problems that include questions in genomics, medicine, genome engineering, sequencing technology, molecular biology, genetics, and others.
Our students are actively involved in high-profile research, and have developed very widely-used bioinformatics software systems such as Bowtie, Tophat, and Cufflinks. The work they do with Hopkins faculty prepares them to go on to postdoctoral and tenure track faculty positions at top-ranked universities including (in recent years) Harvard, MIT, Carnegie Mellon, and Brown.
Students in computational biology at Hopkins can enroll in one of four different Ph.D. programs. These include Biomedical Engineering, ranked #1 in the nation; Biostatistics, ranked #5 in the nation; Biology, ranked #5 in the nation; and the rapidly growing Computer Science Department, which just moved into a state-of-the-art new building, Malone Hall.
CCB faculty have appointments in each of these programs, and some of us maintain appointments in multiple programs. To determine which program fits your interests and background, browse the course lists below. Each program has a separate application process; please apply specifically to the departments you're interested in. Applications to multiple programs are permitted, but if you're not certain, we encourage you to contact potential faculty advisors before you apply. Wherever you apply, make it clear that your interest is Computational Biology.
Sample Course Offerings for Ph.D. students in Computational Biology
Department of Computer Science, Whiting School of Engineering
Computer Science at Johns Hopkins University is a diverse, collaborative, and intensely research-focused department. The Department just moved into a brand new, state-of-the-art research building, Malone Hall, designed around the needs of students and faculty. See the video highlighting the new building and some of our students here. The faculty represent a broad spectrum of disciplines encompassing core computer science and many cross-disciplinary areas including Computational Biology and Medicine, Information Security, Machine Learning, Data Intensive Computing, Computer-Integrated Surgery, and Natural Language Processing
A total of 8 courses are required, and a typical load is 3 courses per semester. See the CS Department website for details. Courses that might interest a computational biology student include:600.639 Computational Genomics
580.689 Computational Personal Genomics
600.624 Advanced Topics in Data-Intensive Computing
600.676 Machine Learning: Data to Models
600.640 Frontiers of Sequencing Data Analysis
600.663 Pattern Matching Algorithms
600.666 Information Extraction
600.688 Foundations of Computational Biology and Bioinformatics II
Plus electives that might include:600.463 Algorithms I
600.465 Natural Language Processing
600.475 Machine Learning
600.416 Database Systems
600.420 Parallel Programming
600.615 Big Data, Small Languages, Scalable Systems
600.466 Information Retrieval and Web Agents
For the Computer Science Ph.D., 2 out of the required 8 classes can be taken outside the Department. These may include any of the courses in the BME, Biostatistics, and Biology programs listed on this page.
Department of Biomedical Engineering, Whiting School of Engineering
The Johns Hopkins Department of Biomedical Engineering (BME), widely regarded as the top program of its kind in the world and ranked #1 in the nation by U.S. News, is dedicated to solving important clinical problems. At the intersection of inquiry and discovery, the department integrates biology, medicine, and engineering and draws upon the considerable strengths and talents of the Johns Hopkins Schools of Engineering and Medicine. See the BME Ph.D. program website for details beyond the brief summary here. NOTE: the Fall 2016 deadline for applications is early this year: December 1, 2015.
The BME course requirements are very flexible, allowing Computational Biology students to craft a program designed for their interests. 36 credits (typically 10-12 courses) are required for the Ph.D., with 18 in life sciences and 18 in quantitative sciences. Quantitative sciences include engineering, computer science, applied mathematics, computational biology, and biostatistics. A Ph.D. student in computational biology might be interested in these courses:
580.588 Foundations of Computational Biology and Bioinformatics II
580.689 Computational Personal Genomics
550.560 Statistical Models in Molecular Medicine
580.423 Systems Bioengineering III (systems biology)
600.639 Computational Genomics
Other courses that might be part of a Ph.D. in BME include:
580.421 Systems Bioengineering I (cardiovascular)
580.422 Systems Bioengineering II (neuroscience)
540.409 Modeling Dynamics and Control for Chemical and Biological Systems
520.610 Computational Functional Genomics
520.636 Feedback Control in Biological Signaling Pathways
540.659 Bioengineering in Regenerative Medicine
580.639 Models of Neuron
580.682 Computational Models of the Cardiac Myocyte
580.690 Systems Biology of Cell Regulation
140.751-756 Advanced Methods in Biostatistics
Department of Biostatistics, Bloomberg School of Public Health
Johns Hopkins Biostatistics is the oldest department of its kind in the world and has long been considered as one of the best. It is ranked #5 in the nation by U.S. News .
At least 18 credits required outside the Dept of Biostatistics, at least 9 of these in the School of Public Health. See the Department website for details.
All students in the Biostatistics Ph.D. program have to complete the core requirements:
- A two-year sequence on biostatistical methodology (140.751-756)
- A two-year sequence on probability and the foundations and theory of statistical science (550.620-621, 140.673-674, 140.771-772);
- Principles of Epidemiology (340.601)
In addition, students in computational biology might take:
- 140.776.01 STATISTICAL COMPUTING (3 credits)
- 140.638.01 ANALYSIS OF BIOLOGICAL SEQUENCES (3 credits)
- 140.644.01 STATISTICAL MACHINE LEARNING: METHODS, THEORY, AND APPLICATIONS (4 credits)
- 140.688.01 STATISTICS FOR GENOMICS (3 credits)
Further courses might include 2-3 courses in Computer Science, BME, or Biology listed on this page.
Department of Biology, Krieger School of Arts and Sciences
The Hopkins Biology Graduate Program, founded in 1876, is the oldest Biology graduate school in the country. People like Thomas Morgan, E. B. Wilson, Edwin Conklin and Ross Harrison, were part of the initial graduate classes when the program was first founded. Hopkins is ranked #5 in the nation in Biological Sciences by U.S. News
Quantitative and computational biology are an integral part of the CMDB training program. During the first semester students attend Quantitative Biology Bootcamp, a one week intensive course in using computational tools and programming for biological data analysis. Two of our core courses - Graduate Biophysical Chemistry and Genomes and Development - each have an associated computational lab component.
Ph.D. in Cell, Molecular, Developmental Biology, and Biophysics (CMDB):
The CMDB core includes the following courses:
020.607 Quantitative Biology Bootcamp
020.674 Graduate Biophysical Chemistry
020.686 Advanced Cell Biology
020.637 Genomes and Development
020.668 Advanced Molecular Biology
Electives include courses such as:
020.606 Molecular Evolution
020.620 Stem Cells
020.630 Human Genetics
020.640 Epigenetics & Chromosome Dynamics
020.650 Eukaryotic Molecular Biology
Students in computational biology can use their electives to take more computationally intensive courses. You have considerable flexibility to design a program of study with your Ph.D. advisor.