BIO 472H1S - COMPUTATIONAL GENOMICS AND BIOINFORMATICS - DOC - DOC

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					                CSB 472H1S - COMPUTATIONAL GENOMICS AND BIOINFORMATICS
                                        24L, 12T


Lecturers:
Prof. N. Provart (Team Leader)                                              nicholas.provart@utoronto.ca
Prof. D. Guttman                                                              david.guttman@utoronto.ca


Exclusion: BCH 441H1

Prerequisites: BIO 230H1/(240H1, 241H1)/250Y1/255H1/255Y1

Recommended preparation: BIO 260H1/HMB 265H1

Computational genomics and bioinformatics provide us with tools to extract biological information from
complex genomic data. We are now able to produce vast amounts of genomic data, which are simply
meaningless characters without sophisticated analysis methods. CSB472 will teach you the fundamentals
of analyzing genomic data. This course emphasizes understanding how core bioinformatic analyses work,
the strengths and weaknesses of related methods, and the important parameters embedded in these
analyses. CSB472 is not an applied methods course, nor a course to for developing new bioinformatic tools.
We will examine the fundamentals of pairwise and multiple sequence alignment, phylogenetic analyses,
genome annotation, gene prediction, and gene expression data analysis. Theoretical, applied, and
statistical issues will be addressed. An important component of this course involves learning introductory
PERL scripting. A basic understanding of this very straightforward scripting language greatly facilitates
bioinformatics analysis, and is an essential skill for anyone wishing to pursue work in this area. PERL
scripting will be taught in a one hour tutorial / computer lab which follows each lecture. No prior
programming experience is required. We will also devote some tutorials to hands-on analysis of genomic
data. This is an advanced course with a strong genetics emphasis meant for Biology and Human
Biology/GGB specialists/majors.

Required text: Zvelebil & Baum 2008 Understanding Bioinformatics. Garland Science, New York.

Evaluation: Four assignments (40%), midterm (30%), final (30%)

				
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