CS 557: Computational Systems Biology Spring 2015

Course Information:

Course Summary: Computational Systems Biology is a research oriented graduate level course, which focusses on recent computational problems in biological systems. Topics include computational methods for understanding and reconstructing biological networks; microRNA target prediction; host-pathogen interactions; phenotype prediction based on systems biology approaches. In each of these cases, we will focus on available biological data and methods for solving the pertinent computational problem. The methods of the course will draw from machine learning, data mining, time series analysis, etc. No background in biology is assumed. Background in basic probability and statistics, machine learning and experience in programming are required.

For other details please refer to the course syllabus [PDF] and the course page for further details.

Text Book:

No required text book. We will be extensively make use of published scientific literature:

Recommend sources:

· Conference proceedings: ICSB, RECOMB, ISMB, PSB, NIPS, ICML, KDD, ECCB, etc.

· Comp bio journals: Bioinformatics, Plos Computational Biology, BMC Systems Biology, etc

· Biology Journals: Nature, Science, Cell, Molecular Systems Biology, PNAS, NAR, Genome Biology, Genome Research, PLoS series,etc

Course website:

We will be using Moodle. Please check regularly the Moodle page of the course for lecture notes, readings, discussions and announcements.