CS 557: Computational Systems Biology Spring 2015 Course
Information: Instructor: Öznur Taştan 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: ˇ
Conference proceedings: ICSB, RECOMB, ISMB,
PSB, NIPS, ICML, KDD, ECCB, etc. ˇ
Comp bio journals: Bioinformatics, Plos Computational Biology, BMC Systems Biology, etc ˇ
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. |