Optional Focuses

CBB graduate students (Ph.D. or M.S.) may elect to pursue an optional focus in Biomedical Data Science or in Translational Informatics and should contact the department registrar if interested. Focuses may be selected at any time and the main requirements are specific coursework and a project that focuses on the relevant topic. These courses can be considered part of the primary CBB curriculum requirements.

Biomedical Data Science

This focus exposes students to data science training and educational initiatives at Yale. Its initial direction is big data analytics of large medical claims and clinical datasets. Students may opt to participate in research opportunities within the Yale Center for Outcomes Research and Evaluation (CORE, Prof. Krumholz, director). CORE maintains its dedicated BD2K division, which includes many of the core training grant faculty (Profs. Zhao, Brandt and Gerstein). Students have access to a myriad of data sets, dedicated and secured server infrastructure, program management staff assisting in data familiarization, and may attend a BD2K seminar.

CORE is one of many ongoing data science initiatives at Yale, which also includes the VA’s PRIME COIN (Brandt, Justice), the Yale Institute for Network Sciences (Gerstein), and emerging data science initiatives at the Department for Statistics and Data Science (Zhao).

At least four courses taken must have a major focus on biomedical data sciences. There are many such courses, including:

  • CPSC 365b: Algorithms
  • CPSC 462: Graphs and Networks
  • CPSC 540b: Numerical Computation
  • MATH 244ab: Discrete Mathematics
  • MATH 246ab: Ordinary Differential Equations
  • S&DS 530ab: Data Exploration and Analysis
  • S&DS 538a: Probability and Statistics
  • S&DS 541a: Probability Theory
  • S&DS 542b: Theory of Statistics
  • S&DS 551b: Stochastic Processes
  • S&DS 610a: Statistical Inference
  • S&DS 612a: Linear Models
  • S&DS 660: Multivariate Statistical Methods
  • S&DS 661b: Data Analysis
  • S&DS 665: Data Mining and Machine Learning

Translational Informatics

Translational research is concerned with bringing bioscience research discoveries into patient care. This 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. The overall CBB curriculum is unchanged, but the Translational Informatics focus makes the following specific course requirements.

The following courses must be taken (in line with the standard CBB requirements):

  • CB&B 740a: Introduction to Health Informatics
  • CB&B 750b: Core Topics in Biomedical Informatics
  • CB&B 752b: Biomedical Data Science: Mining and Modeling

At least two of the other courses taken must have a major focus on clinical medicine and/or disease. There are many such courses, including:

  • BIS 540a: Fundamentals of Clinical Trials
  • CBIO 600a/601b: Science at the Frontiers of Medicine
  • GENE 500b: Principles of Human Genetics
  • IBIO 530a: Biology of the Immune System
  • NSCI 507b: Cellular and Molecular Mechanisms of Neurological Disease
  • PATH 650b: Cellular & Molecular Biology of Cancer