From molecules to organs, formulas to models
Johns Hopkins University Program in Multi-Scale Computational Biology
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Curriculum

Expected background
The training program draws students from a variety of backgrounds in the sciences and in engineering, reflecting the equally diverse composition of the Institute’s faculty. Applications are welcomed from students with degrees in chemical, mechanical, electrical, and computer engineering, applied mathematics, physics, biophysics, chemistry, biochemistry, and other related disciplines.

Professor Iglesias with a grad studentTo accommodate the diverse background of our students, we have flexible course requirements tailored specifically to the interests and background of our students. We strongly recommend that students fulfill requirements in introductory general chemistry and organic chemistry, introductory physics and calculus before joining the program in order to be able to participate fully in the first year courses.

Course work
The principles, methods, and tools for multi-scale modeling of biological systems are drawn from the disciplines of biology, chemistry, biophysics, mathematics, computer science, and chemical, mechanical, electrical, and biomedical engineering. Consequently our curriculum is correspondingly broad. However, the number of required courses is kept to a minimum. During their first year students are required to complete two semester-long survey courses. The first course focuses on fundamental concepts of biochemistry, cell and molecular biology. The second course introduces engineering analysis, numerical methods and simulations. More comprehensive coverage of topics in these courses can be found in complementary specialized graduate courses.

During the first two years, students are required to complete 6 other courses from a large selection that includes courses in biochemistry, cell biology, molecular biology, physical chemistry of biological macromolecules, proteins and nucleic acids, protein solution thermodynamics, statistical mechanics in biological systems, fundamentals of membrane biology, computational mechanics of biological macromolecules, biomolecular and nanoscale simulations, computational biology and bioinformatics, signal control in biological signaling pathways, and systems biology of cell regulation.