Seeking gene relationships in gene expression data using support vector machine regression-0

Morley et al. [2]. The Affymetrix probeset IDs are listed in parentheses.<p><b>Copyright information:</b></p><p>Taken from "Seeking gene relationships in gene expression data using support vector machine regression"</p><p>http://www.biomedcentral.com/1753-6561/1/S1/S51</p><p>BMC Proceedings 2007;1(Suppl 1):S51-S51.</p><p>Published online 18 Dec 2007</p><p>PMCID:PMC2367560.</p><p></p

Seeking gene relationships in gene expression data using support vector machine regression-4

The gene pool hit a group of genes that formed set A. The pathway reconstruction was done using 4.0 (Ariadne Genomics, Inc.).<p><b>Copyright information:</b></p><p>Taken from "Seeking gene relationships in gene expression data using support vector machine regression"</p><p>http://www.biomedcentral.com/1753-6561/1/S1/S51</p><p>BMC Proceedings 2007;1(Suppl 1):S51-S51.</p><p>Published online 18 Dec 2007</p><p>PMCID:PMC2367560.</p><p></p

Seeking gene relationships in gene expression data using support vector machine regression-2

Protein genes. Group A is the genes selected for the SVMR training set. Groups B and C are the genes that were targeted and captured in two separate SVMR searches.<p><b>Copyright information:</b></p><p>Taken from "Seeking gene relationships in gene expression data using support vector machine regression"</p><p>http://www.biomedcentral.com/1753-6561/1/S1/S51</p><p>BMC Proceedings 2007;1(Suppl 1):S51-S51.</p><p>Published online 18 Dec 2007</p><p>PMCID:PMC2367560.</p><p></p

Seeking gene relationships in gene expression data using support vector machine regression-1

Iological group, ribosomal proteins. A1 and A2 are from the same gene, . Correlation coefficients for expression of genes and are > 0.987, but they appear to share no direct biological relationship, even though their NPL LOD score distributions show high similarity as well.<p><b>Copyright information:</b></p><p>Taken from "Seeking gene relationships in gene expression data using support vector machine regression"</p><p>http://www.biomedcentral.com/1753-6561/1/S1/S51</p><p>BMC Proceedings 2007;1(Suppl 1):S51-S51.</p><p>Published online 18 Dec 2007</p><p>PMCID:PMC2367560.</p><p></p