[BiO BB] Courses: Gene Expression Analysis and Biostatistics

[J.W. Bizzaro]

Greetings,

The following courses are being offered at Bioinformatics.Org this month:

Gene Expression Analysis; Feb 18-22, 2008

This course helps to demystify Affymetrix analysis so that any researcher can take the basic steps to go from a chip image to a list of genes that are up- or down-regulated in an experiment. Various tools will be covered, e.g. GCOS, Excel, MATLAB, and free tools like R and Dchip. It is geared towards researchers who conduct microarray experiments to study genome-wide expression changes and understand the underlying mechanisms of gene regulation in samples of interest. Most scientists are not able to analyze the resulting data themselves. They are not able to get desired results using traditional tools like Microsoft Word and Excel, or with advanced software provided by commercial vendors. The freeware solutions come either with a steep learning curve or as black-box interfaces that provide limited functionality with little or no technical support. In the midst of all this is the fundamental lack of understanding among scientists on how the technology works and what the fundam
ental parts of the analysis are.

FOR MORE INFORMATION:
http://wiki.bioinformatics.org/BI201A_Gene_Expression_Analysis

Biostatistics: Distributions, Tests and Graphics; Feb 25-29, 2008

The various statistical distributions covered will help you know when assumptions can be made about a normal distribution and how to test whether or not these assumptions are true. Essential descriptive statistics are reviewed and then used in various situations to calculate background, noise, normalization and thresholding. Additionally, hypothesis testing is introduced so that you can assess groups of observations for a particular parameter and calculate whether or not the difference between groups is significant. Data visualization using various graphs will also be reviewed. Armed with these techniques, you will be able to better deal with the challenges of data analysis. Plus, you'll be able to understand and interpret data at a more fundamental level and draw the correct conclusions about them.

FOR MORE INFORMATION:
http://wiki.bioinformatics.org/MA101A_Distributions,_Tests_and_Graphics

Cheers,
Jeff
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J.W. Bizzaro
Bioinformatics Organization, Inc. (Bioinformatics.Org)
E-mail: jeff at bioinformatics.org
Phone:  +1 508 890 8600
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