Department website: https://icm.jhu.edu/
The Institute for Computational Medicine (ICM) offers an undergraduate minor in Computational Medicine, the first educational program in CM, reflecting Johns Hopkins University’s leadership in this field. Like the ICM, the undergraduate minor in Computational Medicine is integrative and multidisciplinary. The ICM Core Faculty who serve as advisors to the undergraduate minor hold primary and joint appointments in multiple Johns Hopkins University departments and schools including Biomedical Engineering, Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Applied Mathematics and Statistics (WSE); Neurosurgery, Emergency Medicine, Medicine, and the Divisions of Cardiology and Health Sciences Informatics (SOM); and Health Policy and Management (BSPH).
With a minor in CM, undergraduates gain a solid grounding in the development and application of computational methods in key areas of medicine. Specifically, undergraduates will understand how mathematical models can be constructed from biophysical laws or experimental data, and how predictions from these models facilitate the diagnosis and treatment of a disease. Undergraduates will become conversant with a wide variety of statistical, deterministic, and stochastic modeling methods, skills that are essential to the advancement of modern medicine, and are prized both in academic research and industrial research.
Declaring the Minor
Students interested in the minor should visit the Institute for Computational Medicine website for instructions on how to declare the minor.
The information below describes the academic requirements for students entering JHU as degree-seeking students in Fall 2025. Students who entered JHU as degree-seeking students prior to Fall 2025 should view the appropriate archived catalogue.
MINOR PREREQUISITES
MATHEMATICS COURSES
Code | Title | Credits |
---|---|---|
AS.110.108 | Calculus I (Physical Sciences & Engineering) | 4 |
AS.110.109 | Calculus II (For Physical Sciences and Engineering) | 4 |
One additional course from Math (AS.110) or Applied Math & Statistics (EN.553) department | 3-4 | |
Probability and Statistics Course. Choose one from the following: | 3-8 | |
Statistical Modeling and Analysis with Python | ||
Intermediate Probability and Statistics | ||
Probability and Mathematical Statistics | ||
Honors Probability and Honors Mathematical Statistics | ||
Total Credits | 14-20 |
BIOLOGICIAL SCIENCE COURSE
Code | Title | Credits |
---|---|---|
Complete one of the following: | 3-4 | |
AS.020.303 | Genetics | 3 |
AS.020.305 | Biochemistry | 3 |
AS.080.305 | Neuroscience: Cellular and Systems I | 3 |
AS.171.310 | Biological Physics | 4 |
AS.250.253 | Protein Engineering and Biochemistry Lab | 3 |
AS.250.315 | Biochemistry I | 3 |
EN.580.221 | Biochemistry and Molecular Engineering | 4 |
Total Credits | 3-4 |
COMPUTER PROGRAMMING
Code | Title | Credits |
---|---|---|
Complete one of the following: | ||
EN.500.112 | Gateway Computing: JAVA | 3 |
or EN.500.113 | Gateway Computing: Python | |
EN.553.385 | Introduction to Computational Mathematics | 4 |
EN.601.220 | Intermediate Programming | 4 |
EN.601.226 | Data Structures | 4 |
Total Credits | 3-4 |
MINOR REQUIREMENTS
In addition to the prerequisites, the CM minor requires 18 credits. Grades of C- or higher are required for all courses. No Satisfactory/Unsatisfactory (S/U) grade is accepted.
CORE COURSES
Code | Title | Credits |
---|---|---|
EN.580.431 | Introduction to Computational Medicine: Imaging | 2 |
EN.580.433 | Introduction to Computational Medicine: The Physiome | 2 |
Complete one course from the following: | 3-4 | |
Mathematical and Computational Foundations of Data Science | ||
Computational Molecular Medicine | ||
Systems Pharmacology and Personalized Medicine | ||
Computational Stem Cell Biology | ||
Computing the Transcriptome | ||
Foundations of Computational Biology and Bioinformatics | ||
Computational Genomics: Applied Comparative Genomics | ||
Data Science for Public Health I | ||
or PH.140.629 | Data Science for Public Health II | |
Total Credits | 7-8 |
ELECTIVE COURSES
No more than 3 independent research credits in computational medicine may be applied at the advisor's discretion. A course may not count for multiple requirements toward the minor. At least one course must be outside of the student's primary major department.
Code | Title | Credits |
---|---|---|
At least two courses from M Designation (see below for course listings) | ||
At least one course from C Designation (see below for course listings) | ||
Total Credits | 10-11 |
ELECTIVE COURSE LISTINGS
Significant Biology/Medicine Component (M)
Code | Title | Credits |
---|---|---|
EN.520.621 | Introduction To Nonlinear Systems | 3 |
EN.530.343 | Design and Analysis of Dynamical Systems | 3 |
EN.530.410 | Biomechanics of the Cell | 3 |
EN.530.616 | Introduction to Linear Systems Theory | 3 |
EN.530.676 | Locomotion Dynamics & Control | 3 |
EN.540.414 | Computational Protein Structure Prediction and Design | 3 |
EN.540.421 | Project in Design: Pharmacodynamics | 3 |
EN.540.433 | Pharmacokinetics and Pharmacodynamics | 3 |
EN.540.438 | Advanced Topics in Pharmacokinetics and Pharmacodynamics I | 3 |
EN.553.391 | 4 | |
EN.553.426 | Introduction to Stochastic Processes | 4 |
EN.580.430 | Systems Pharmacology and Personalized Medicine | 4 |
EN.580.435 | Applied Bioelectrical Engineering | 3 |
EN.580.439 | Models of the Neuron | 4 |
EN.580.447 | Computational Stem Cell Biology | 3 |
EN.580.448 | Computational Genomics: Data Analysis | 3 |
EN.580.460 | Epigenetics at the Crossroads of Genes and the Environment | 2 |
EN.580.462 | Representations of Choice | 3 |
EN.580.464 | Advanced Data Science for Biomedical Engineering | 4 |
EN.580.473 | Dynamic Modeling of Infectious Diseases in Patients and Populations | 2 |
EN.580.480 | Precision Care Medicine I | 4 |
EN.580.481 | Precision Care Medicine II | 4 |
EN.580.488 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.561 | Advanced Focus Area Research | 3 |
EN.580.689 | Modern Optical Microscopy: Theory and Practice | 3 |
EN.601.350 | Genomic Data Science | 3 |
EN.601.447 | Computational Genomics: Sequences | 3 |
EN.601.449 | Computational Genomics: Applied Comparative Genomics | 3 |
EN.601.649 | Computational Genomics: Applied Comparative Genomics | 3 |
EN.660.347 | Action Lab | 3 |
ME.250.771 | Introduction to Precision Medicine Data Analysis | 1.5 |
Significant Computational Component (C)
Code | Title | Credits |
---|---|---|
AS.050.375 | Probabilistic Models of the Visual Cortex | 3 |
AS.250.302 | Modeling the Living Cell | 4 |
EN.520.353 | Control Systems | 4 |
EN.520.432 | Medical Imaging Systems | 3 |
EN.520.433 | Medical Image Analysis | 3 |
EN.520.439 | Machine Learning for Medical Applications | 3 |
EN.520.621 | Introduction To Nonlinear Systems | 3 |
EN.530.343 | Design and Analysis of Dynamical Systems | 3 |
EN.530.410 | Biomechanics of the Cell | 3 |
EN.530.616 | Introduction to Linear Systems Theory | 3 |
EN.540.409 | Dynamic Modeling and Control | 4 |
EN.540.414 | Computational Protein Structure Prediction and Design | 3 |
EN.540.421 | Project in Design: Pharmacodynamics | 3 |
EN.540.433 | Pharmacokinetics and Pharmacodynamics | 3 |
EN.540.438 | Advanced Topics in Pharmacokinetics and Pharmacodynamics I | 3 |
EN.540.638 | Advanced Topics in Pharmacokinetics and Pharmacodynamics I | 3 |
EN.553.361 | Introduction to Optimization I | 4 |
EN.553.391 | 4 | |
EN.553.426 | Introduction to Stochastic Processes | 4 |
EN.553.430 | Mathematical Statistics | 4 |
EN.553.436 | Introduction to Data Science | 4 |
EN.553.492 | Mathematical Biology | 3 |
EN.580.430 | Systems Pharmacology and Personalized Medicine | 4 |
EN.580.437 | Biomedical Data Design | 4 |
EN.580.438 | Biomedical Data Design II | 4 |
EN.580.439 | Models of the Neuron | 4 |
EN.580.447 | Computational Stem Cell Biology | 3 |
EN.580.460 | Epigenetics at the Crossroads of Genes and the Environment | 2 |
EN.580.462 | Representations of Choice | 3 |
EN.580.464 | Advanced Data Science for Biomedical Engineering | 4 |
EN.580.473 | Dynamic Modeling of Infectious Diseases in Patients and Populations | 2 |
EN.580.480 | Precision Care Medicine I | 4 |
EN.580.481 | Precision Care Medicine II | 4 |
EN.580.488 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.491 | Learning, Estimation and Control | 3 |
EN.580.689 | Modern Optical Microscopy: Theory and Practice | 3 |
EN.601.350 | Genomic Data Science | 3 |
EN.601.447 | Computational Genomics: Sequences | 3 |
EN.601.455 | Computer Integrated Surgery I | 4 |
EN.601.461 | Computer Vision | 3 |
EN.601.475 | Machine Learning | 3 |
EN.601.482 | Machine Learning: Deep Learning | 4 |
EN.601.649 | Computational Genomics: Applied Comparative Genomics | 3 |
EN.601.455 | Computer Integrated Surgery I | 4 |
EN.601.456 | Computer Integrated Surgery II | 3 |
EN.601.496 | Computer Integrated Surgery II - Teams | 3 |
PH.340.677 | Infectious Disease Dynamics: Theoretical and Computational Approaches | 4 |
DISTINGUISHED SEMINAR SERIES
Students enrolled in the Computational Medicine minor are required to attend six ICM Distinguished Seminars in person prior to graduation. For seminar details and attendance instructions, students should visit the Institute for Computational Medicine website.