Abstract #301986

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JSM 2002 Abstract #301986
Activity Number: 111
Type: Contributed
Date/Time: Monday, August 12, 2002 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section*
Abstract - #301986
Title: A Summary of the Various Statistical Methods Currently in Use for the Analysis of Gene Expression Microarray Data
Author(s): Amy Collins Licata*+ and Georgiy Bobashev
Affiliation(s): RTI International and RTI International
Address: 3040 Cornwallis Rd., RTP, NC, 27709, USA
Keywords: pattern identification ; genetic network ; clustering ; classification ; similarity measures
Abstract:

Microarrays generate a large volume of experimental data and many methods, such as clustering and classification, can be used to analyze this data. Initial investigation through exploratory analysis provides great insight into the data by detecting structures and patterns. After patterns have been identified, they can be used for both discovery and prediction of genes through various methods. Although pattern recognition methods incorporate some prior information, their use is limited because they do not provide an explanation for the underlying mechanism of genetic networks. Recently, many attempts have been made to use microarray data for uncovering these mechanisms. From initial investigative studies to developing genetic networks, this paper discusses an assortment of statistical methods that are currently used to analyze gene expression microarray data.

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Revised March 2002