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Prediction of gene function by genome-scale expression analysis: prostate cancer-associated genes
M G Walker1, W Volkmuth, E Sprinzak
1Incyte Pharmaceuticals, Palo Alto, California 94304, USA. mwalker@incyte.com
Genome Research
|December 30, 1999
Summary
Researchers discovered hundreds of novel disease-associated genes using Guilt-by-Association (GBA). This method identified new targets for cancer and other diseases, including eight genes linked to prostate cancer.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Identifying novel disease-associated genes is crucial for understanding disease mechanisms and developing new therapies.
- Traditional methods like homology searches are limited in discovering genes with no sequence similarity to known genes.
Purpose of the Study:
- To identify novel genes associated with various human diseases using a novel computational approach.
- To discover previously unidentified genes linked to cancer, inflammation, and other disease processes.
Main Methods:
- Development and application of the Guilt-by-Association (GBA) method, a combinatoric measure of gene expression association.
- Analysis of gene expression patterns for 40,000 human genes across 522 cDNA libraries.
Main Results:
- Discovery of several hundred previously unidentified disease-associated genes.
- Identification of eight novel genes strongly associated with prostate cancer, showing high linkage to known diagnostic genes.
- The majority of discovered genes lack sequence similarity to known genes, highlighting the novelty of the findings.
Conclusions:
- The Guilt-by-Association (GBA) method is effective in identifying novel disease-associated genes, including those without sequence homology to known genes.
- The identified genes, particularly those linked to prostate cancer, represent promising targets for pharmaceutical research and development.