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Article #387Bioinformatics for gene expression analysis
From: Heather Vincent
Date: Mon, 14 Feb 2011 08:09
Date: Mon, 14 Feb 2011 08:09
27 lines
3700 bytes
3700 bytes
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@cs.man.ac.uk).
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