The Institute for Computational Medicine (ICM) is proud to offer an undergraduate minor in Computational Medicine, the first educational program in CM, reflecting Johns Hopkins University’s leadership in this field. Like the ICM itself, the undergraduate minor in Computational Medicine is integrative and multidisciplinary. The 19 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 will have a solid grounding in the development and application of computational methods in multiple 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 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.
CM research at ICM is sub-divided into four key areas: Computational Molecular Medicine; Computational Physiological Medicine; Computational Anatomy; Computational Healthcare. Techniques for and applications in each of these four key subareas are introduced during the required core courses, exposingt undergraduates to the breadth of Computational Medicine, and enabling each student to identify a preferred area of interest:
- Computational Physiological Medicine develops mechanistic models of biological systems in disease, and applies the insights gained from these models to develop improved diagnostics and therapies. Therapies could be diverse drugs, electrical stimulation, mechanical support devices and more.
- Computational Molecular Medicine harnesses the enormous amount of disease-relevant data produced by next-generation sequencing, microarray and proteomic experiments of large patient cohorts, using statistical models to identify the drivers of disease and the susceptible links in disease networks.
- Computational Anatomy uses medical imaging to analyze the variation in structure of human organs in health and disease. Such image analysis has been integrated into clinical workflows to assist in the diagnosis and prognosis of complex diseases.
- Computational Healthcare is an emerging field devoted to understanding populations of patients and their interaction with all aspects of the healthcare process.
CM is distinct from Computational Biology in its focus on human health, disease, and treatment; translation to and application in the clinic is a near-term goal of all CM research. Applications of CM are as broad as medicine itself, and include: identification of optimal drugs using associated genomic and proteomic biomarkers; discovery of image-based biomarkers for diagnosis and prognosis; design and dynamic adjustment of individualized non-drug therapies such as deep brain stimulation, cardiac stimulation, and cochlear implants; modeling and learning from patient EHR data to improve patient outcomes and efficiency of care; optimization of healthcare policy decisions by quantitative analysis; and more. CM is one of the pillars of the University’s Strategic Initiative in Individualized Health.
Computational Medicine (CM) is an emerging discipline devoted to the development of quantitative approaches for understanding the mechanisms, diagnosis and treatment of human disease through applications of mathematics, engineering and computational science. The core approach of CM is to develop computational models of the molecular biology, physiology, and anatomy of disease, and apply these models to improve patient care. CM approaches can provide insight into and across many areas of biology, including genetics, genomics, molecular networks, cellular and tissue physiology, organ systems, and whole body pharmacology.
Before attempting the minor, undergraduates will have taken the following courses:
- Calculus I
- Calculus II
- Probability and Statistics: either a single course covering both (e.g. EN.550.310), or a course devoted to each (e.g., EN.550.420 and EN.550.430) – this may be taken concurrent with core course EN.580.431
- At least one (1) additional course in mathematics or applied mathematics (at least 3 credits)
- At least one (1) computer programming course (at least 3 credits)
- At least one (1) biological sciences course (at least 3 credits)
EN.580.431 is a newly developed class that covers computational anatomy and physiology and will be jointly taught by ICM faculty from multiple departments.
The second semester is an expansion of EN.580.431, with emphasis on molecular medicine and computational healthcare. EN.550.450 requires background in probability theory and statistics. Students requiring additional training in these areas may do this course work in their junior year, and take this course in their senior year.
Distinguished Seminar Series
Students in the minor ARE REQUIRED to register at least twice for the ICM Distinguished Seminar Series in Computational Medicine (EN.580.737). Eight distinguished seminars are held each academic school year, four each semester (unless otherwise advertised). Students enrolled in the minor are REQUIRED to attend no less than 6 such seminars in person. Attendance is recorded*.
This is recognized as a P/F (satisfactory/unsatisfactory) course. Enrolled students must receive an "S" grade for both semesters of enrollment. Contact ICM Administrative Office for further details.
Following satisfaction of the prerequisites, to complete the minor, undergraduates must take at least 6 CM courses totaling at least 18 credits. This includes two one-semester core courses plus four approved courses selected from those listed below. The following restrictions are noted:
- At most 3 of the 18 credits can consist of independent research in Computational Medicine, as defined and agreed to in advance by the minor advisor;
- The 18 credits will all be at 300-level or above, and courses must be passed at a C- level or above;
- At least 2 non-core/elective courses must be outside student’s home department
- At least 2 non-core/elective courses must have a substantial biology or medicine component, as identified in the list below with an (M) designation.
- At least 1 non-core/elective course must have a substantial computational component, as identified in the list below with an (C) designation
- All courses must be passed at a C- level or above
|Electrical and Computer Engineering|
|EN.520.315||Introduction to Information Processing of Sensory Signals||3|
|EN.520.432||Medical Imaging Systems (M)||3|
|EN.520.601||Introduction to Linear Systems Theory||3|
|EN.520.621||Introduction To Nonlinear Systems||3|
|EN.530.343||Design and Analysis of Dynamical Systems||4|
|EN.530.676||Locomotion in Mechanical and Biological Systems (M)||3|
|Chemical and Biomolecular Engineering|
|EN.540.400||Project in Design: Pharmacokinetics (MC)||3|
|EN.540.409||Dynamic Modeling and Control (C)||4|
|EN.540.421||Project in Design: Pharmacodynamics (MC)||3|
|Applied Mathematics and Statistics|
|EN.550.420||Introduction to Probability||4|
|EN.550.426||Introduction to Stochastic Processes||4|
|EN.550.430||Introduction to Statistics||4|
|EN.550.436||Data Mining (C)||4|
|EN.560.447||Systems Science for a Dynamic World||3|
|EN.580.430||Systems Pharmacology and Personalized Medicine (MC)||3|
|EN.580.460||Theory of Cancer (MC)||3|
|EN.580.468||The Art of Data Science||3.00|
|EN.580.488||Foundations of Computational Biology and Bioinformatics II (MC)||3|
|EN.580.491||Learning Theory (C)||3|
|EN.580.689||Computational Personal Genomics (MC)||3|
|EN.580.694||Statistical Connectomics (MC)||3|
|EN.600.323||Data-Intensive Computing (C)||3|
|EN.600.438||Computational Genomics: Data Analysis (MC)||3.00|
|EN.600.439||Computational Genomics (MC)||3|
|EN.600.340||Introduction to Genomic Research (MC)||3.00|
|EN.600.445||Computer Integrated Surgery I (C)||4|
|EN.600.461||Computer Vision (C)||3|
|EN.600.476||Machine Learning: Data to Models (C)||3|
|EN.600.624||Advanced Topics in Data-Intensive Computing (C)||3|
|EN.600.640||Frontiers of Sequencing Data Analysis (MC)||3|
Declaring the Minor
Interested students should contact Tifphany Cantey, ICM Administrative Coordinator, to receive guidance on declaring the minor:
Specific questions regarding the minor requirements and courses can be directed to Dr. Joshua Vogelstein, Director of Undergraduate Studies for the CM minor.
Director of Institute for Computational Medicine, Director of Center for Cardiovascular Bioinformatics and Modeling, Raj and Neera Singh Professor of Biomedical Engineering
Director of Undergraduate Studies
Joshua T. Vogelstein
Assistant Professor, Dept. of Biomedical Engineering
William S. Anderson
Associate Professor, Dept. of Neurosurgery, Attending Neurosurgeon at The Johns Hopkins Hospital
Associate Professor, Dept. of Biomedical Engineering, Bioinformatics and Computational Biology Lab
Associate Professor, Dept. of Biomedical Engineering, Center for Imaging Sciences
Assistant Research Professor, Dept. of Biomedical Engineering
Assistant Professor, Dept. of Applied Mathematics and Statistics, Center for Imaging Sciences
Professor of Emergency Medicine, Director of Center for Advanced Modeling in the Social, Behavioral and Health Sciences
Feilim Mac Gabhann
Assistant Professor, Dept. of Biomedical Engineering
Professor , Applied Mathematics and Statistics, Center for Imaging Sciences
Associate Professor, Dept. of Biomedical Engineering, The William R. Brody Faculty Scholar
Michael I. Miller
Herschel and Ruth Seder Professor, Dept. of Biomedical Engineering, Director of Center for Imaging Sciences
Professor, Dept. of Mechanical Engineering
Associate Research Professor, Dept. of Biomedical Engineering
Assistant Professor, Dept. of Computer Science
Assistant Professor, Dept. of Biomedical Engineering
Murray B. Sachs Professor, Dept. of Biomedical Engineering
Associate Professor, Dept. of Biomedical Engineering, Computer Science, Mechanical Engineering, and Electrical and Computer Engineering, Director of Vision Dynamics and Learning Lab
Professor and Chair, Dept. of Applied Mathematics and Statistics