800-618-4681 | Request Info
Mobile Menu

RBIF 112

Mathematical Modeling for Bioinformatics

The development of new bioinformatics tools typically involves some form of data modeling, prediction or optimization. This course introduces various modeling and prediction techniques including linear and nonlinear regression, principal component analysis, support vector machines, self-organizing maps, neural networks, set enrichment, Bayesian networks, and model-based analysis.

At the end of the course, students will be able to:

Determine the appropriate method for common data analysis problems.

Assess alternatives if these methods are insufficient.

Interpret the application of commonly used software tools for data modeling, prediction, and optimization.

Compose and present a meaningful report of their analysis.

View upcoming events

View our events calendar for the latest list of upcoming online admissions chats, webinars and other opportunities to get to know GPS programs, faculty and staff.

Get Advice

Brandeis GPS is committed to giving you the support you need to succeed. From the moment you begin the application process to the day you graduate and beyond, our advising team is here to support you. Talk to an enrollment advisor today.

Online Learning

Learn more about our unique approach to online learning and what makes a Brandeis GPS education so engaging.