Translational Bioinformatics - BINF G4006

2:00pm - 3:30pm Mondays and Wednesdays, Fall 2016
Location: TBD, Morningside Campus

Columbia Course Directory | Courses@CU

Pre-requisites

Familiarity with programming in either python or R. Basic Probability.

Course Description

Methods in biomedical data science (i.e. translational bioinformatics) for graduate students and upperclassmen. Students study the statistical and computational algorithms to evaluate large biomedical data, including sequence analysis, application of supervised and unsupervised machine learning, graph theoretic models and network analysis, and chemical informatics. They study how to apply these algorithms to biomedical domains in non-human genetics, human genetics, pharmacology, and public health. Successful completion of the course readies the student for graduate level research in translational bioinformatics

Format

This course will be a hands look at translational bioinformatics research. Students will design and implement their own research project both independently and in collaboration with other students.

Mondays: Lectures on topics in Translational Bioinformatics.
Wednesdays: Students present an update on their project.

Text Books

The textbooks for this course are both freely available.

PLOS Computational Biology: Translational Bioinformatics edited by Maricel Kann, Guest Editor, and Fran Lewitter. If the link doesn't work you this.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Second Edition) by Trevor Hastie, Robert Tibshirani and Jerome Friedman (2009)

Assigned Readings

Login to the Courseworks website to get the week's reading materials.