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Curriculum and Other Requirements for the CBB MS, PhD, and MD/PhD Degrees

This section outlines the current CBB curriculum, and other requirements for the CBB MS and PhD degrees (including students enrolled in Yale’s MD/PhD program). Because of the interdisciplinary nature of the field, entering students are quite heterogeneous in their background and training. A welcoming/advisory committee helps students individually tailor the curriculum to their background and interests. The emphasis is on gaining competency in three broad "core areas":

  •  computational biology and bioinformatics,
  •  biological sciences,
  •  informatics (including computer science, statistics, and applied mathematics).

CBB Curriculum for PhD

Take a minimum of ten courses (10)

General Curriculum Description

Example Translational Informatics Focus Curriculum

Example Biomedical Data Science Focus Curriculum

Three (3) required graduate courses in computational biology and bioinformatics

CBB 750: Core Topics in Biomedical Informatics and Data Science

CBB 750: Core Topics in Biomedical Informatics and Data Science

CBB 740: Topics in Clinical and Translational Informatics

CBB 740: Topics in Clinical and Translational Informatics

CBB 752: Bioinformatics: Practical Application of Simulation and Data Mining

CBB 752: Bioinformatics: Practical Application of Simulation and Data Mining

Two (2) graduate courses in the biological sciences

GENE 500b Principles of Human Genetics

GENE 500b Principles of Human Genetics

PATH 650, Cellular and Molecular Biology of Cancer

MCDB 561, Systems Modeling in Biology


Two (2) graduate courses in areas of informatics

CBB 645, Statistical Methods in Genetics and Bioinformatics

STAT 538, Probability and Statistics

CPSC 537, Introduction to


STAT 665, Data Mining and Machine Learning

Two (2) additional courses in any of the three core areas (which may be undergraduate courses taken to satisfy areas of minimum expected competency)

BIS 540a Fundamentals of Clinical Trials

CPSC 365 Design and Analysis of Algorithms

IBIO 530a Biology of the Immune System

CPSC 462 Graphs and Networks

One (1) year-long graduate course that is three lab rotations over the fall and spring semesters first year, (graded as pass or fail)

CBB 711:Lab Rotation

CBB 711: Lab Rotation

Complete the following Additional Coursework and Activities:

  • Two (2) half-semester graduate seminars (CBB 601b) on research ethics in the 1st and 4th years, (graded as credit or non-credit)
  • Participate in the Biomedical Informatics Teaching Seminar – bi-weekly,
  • Serve as a teaching assistant in two semester courses

Masters Degree (or PhD) Training in “Translational Informatics or Data Science”  for Postdoctoral Fellows in Computational Biology and Bioinformatics (CBB)

Translational research is concerned with bringing bioscience research discoveries into patient care. The CBB Translational Informatics focus emphasizes the intersection of bioinformatics and disease, and includes topics from both bioinformatics and clinical informatics. Examples include 1) research that uses genomic technologies to help better understand the mechanisms of disease, 2) organizing data from the electronic medical record to help define the clinical phenotype of many diseases, 3) building informatics tools that analyze clinical and bioscience data in an integrated fashion, and 4) the computer modeling of disease processes. (See the description of our CBB program for more detail.) Postdoctoral applicants interested in this program should contact Prof. Michael Krauthammer for information as to how to apply.

Master of Health Science (MHS) with a "Clinical Informatics" Focus for Postdoctoral Fellows

Yale School of Medicine now offers a Master of Health Science (MHS) degree with a clinical informatics focus. This degree is designed for postdoctoral informatics fellows who are clinicians. Fellows enrolled for this degree will complete an MHS research project and will also take a variety of courses focused on clinical/ translational research, medical informatics, and related courses and seminars. The specific courses taken by each fellow can be tailored to that individual's background, interests, and career plans. Prof. Shiffman serves as Track Director with Prof. Melnick as Co-Director. The MHS degree is designed to be completed in 2 years.

Coursework required of MHS students in the Clinical Informatics Track is outlined in Table B.

Table B: MHS Clinical Informatics Track Curriculum

CBB 740

Clinical and Translational Informatics

CBB 750

Core Topics in Biomedical Informatics and Data Science

CBB 752

Bioinformatics: Practical Application of Simulation and Data Mining

IMED 630

Ethical and Practical Issues in Clinical Investigation or MBB 601b

IMED 625

Principles of Clinical Research

IMED 645

Introduction to Biostatistics

IMED 665

Writing Your First Grant (Strongly recommended)

Electives (2) courses in consultation with their research advisor, the Pathway Director, and the MHS Degree Advisory Committee that reflects their background and career goals.

Biomedical Informatics Teaching Seminar – bi-weekly

In addition to completing this coursework, the MHS/Clinical Informatics Track student completes and defends a Masters research project focused on some aspect of clinical informatics (see below). A required product of the program is a Master’s thesis averaging 40-80 pages of text.

Eligibility & Application

Qualifications and Selection Criteria

Predoctoral Trainees in the CBB PhD Program 

For our PhD program in Computational Biology and Bioinformatics (CBB), it is important for trainees to have significant academic exposure to both biology and computing. Our selection requirements are flexible, however, since the primary goal is to attract as talented candidates as possible. If necessary, certain trainees may need to make up some coursework at an undergraduate level in areas in which their formal background is weak.

Postdoctoral Fellows 

We want to recruit postdoctoral fellows who have a high-quality educational background and a record of accomplishment as well as a commitment to a career in research informatics. Both clinician and bioscientist postdoctoral trainees should have considerable computer experience and a desire to pursue a research career in biomedical informatics. Computer experience might include formal computer science coursework or significant experience with computer programming and system design, and is evaluated on an individual basis. Research experience is typically demonstrated by research publications.

  • For postdoctoral clinician trainees, we usually give preference to physicians who have completed residency training. Since the most important goal, however, is to attract as high quality trainees as possible, we also consider physicians without full residency training and candidates with other clinical doctoral degrees.
  • For postdoctoral trainees with a PhD in the biosciences, we want candidates who have the appropriate background and interest to devote a research career to biomedical informatics. We recruit such fellows with the help of our bioscience collaborators.

Postdoctoral applications are required to include the applicant's CV, three letters of reference, and a statement of the individual's experience and career goals in Biomedical Informatics. Candidates are interviewed by at least three affiliated faculty members. Preference is given to those individuals who demonstrate a strong commitment to a career in Biomedical Informatics, and to those who have the greatest potential to make significant research contributions to the field. The Co-Directors make final decisions on admissions after review and discussion with the Biomedical Informatics Training Coordinating Committee.