[Molecular-evolution] Bioinformatics for gene expression analysis

Heather Vincent via mol-evol%40net.bio.net (by Heather.Vincent from manchester.ac.uk)
Mon Feb 14 03:09:22 EST 2011


New developments in the high-throughput methods for gene expression 
analysis bring new challenges in data analysis and management.  Error 
models for microarray data have been well studied, but more work is 
still needed on appropriate methods for short-read sequence data.

Moving beyond the pre-processing steps, biological understanding 
requires the integration of expression data with other types of data, 
such as GO categories and KEGG pathways.

The University of Manchester's distance course in microarray data 
analysis 
(http://octette.cs.man.ac.uk/bioinformatics/modules/BIOL61010.html), 
which runs again in March, provides practical experience in both the 
pre-processing and in data integration stages in the analysis. 
Participants will study microarray data in depth, and will also be 
introduced to the most recent methods for transcriptome analysis.

For those interested in learning about data integration in more depth, 
the microarray course is designed to link to our sister course in 
network analysis, Bioinformatics for Systems Biology 
(http://octette.cs.man.ac.uk/bioinformatics/modules/BIOL61820.html). 
Bioinformatics for Systems Biology will run again in October 2011.

There are links to further information on all of our courses here : 
http://octette.cs.man.ac.uk/bioinformatics/modules/index.html  If you 
have any questions, or would like to book a place on a course, please 
contact our office for Advanced Professional Education (ape from cs.man.ac.uk).



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