CBB graduate students (PhD or MS) 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 (see below for details) 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 (not given in 2020-2021)
- CPSC 540b Numerical Computation (not given in 2020-2021)
- 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 (not given in 2020-2021)
- S&DS 661b Data Analysis
- S&DS 665 Data Mining and Machine Learning (not given in 2020-2021)
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 (inline 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 (not given in 2020-2021)
- IBIO 530a Biology of the Immune System
- NSCI 507b Cellular and Molecular Mechanisms of Neurological Disease (not given in 2020-2021)
- PATH 650b Cellular & Molecular Biology of Cancer