Gene network reconstruction from microarray data Export

@article{citeulike:6095885, abstract = {BACKGROUND:Often, software available for biological pathways reconstruction rely on literature search to find links between genes. The aim of this study is to reconstruct gene networks from microarray data, using Graphical Gaussian models.RESULTS:The GeneNet R package was applied to the Eadgene chicken infection data set. No significant edges were found for the list of differentially expressed genes between conditions MM8 and MA8. On the other hand, a large number of significant edges were found among 85 differentially expressed genes between conditions MM8 and MM24.CONCLUSION:Many edges were inferred from the microarray data. Most of them could, however, not be validated using other pathway reconstruction software. This was partly due to the fact that a quite large proportion of the differentially expressed genes were not annotated. Further biological validation is therefore needed for these networks, using for example in vitro invalidation of genes.}, author = {Jaffrezic, Florence and Klopp, Gwenola T.}, citeulike-article-id = {6095885}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/1753-6561-3-S4-S12}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19615112}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19615112}, doi = {10.1186/1753-6561-3-S4-S12}, issn = {1753-6561}, journal = {BMC Proceedings}, keywords = {biological\_pathways, differentially\_expressed\_genes, network\_topology, networks, pathways, reconstruction\_software, regulatory\_pathways, signaling\_pathways}, number = {Suppl 4}, pages = {S12+}, posted-at = {2009-11-10 22:33:57}, priority = {2}, title = {Gene network reconstruction from microarray data}, url = {http://dx.doi.org/10.1186/1753-6561-3-S4-S12}, volume = {3}, year = {2009} }

TY - JOUR ID - citeulike:6095885 L3 - citeulike-article-id:6095885 N2 - BACKGROUND:Often, software available for biological pathways reconstruction rely on literature search to find links between genes. The aim of this study is to reconstruct gene networks from microarray data, using Graphical Gaussian models.RESULTS:The GeneNet R package was applied to the Eadgene chicken infection data set. No significant edges were found for the list of differentially expressed genes between conditions MM8 and MA8. On the other hand, a large number of significant edges were found among 85 differentially expressed genes between conditions MM8 and MM24.CONCLUSION:Many edges were inferred from the microarray data. Most of them could, however, not be validated using other pathway reconstruction software. This was partly due to the fact that a quite large proportion of the differentially expressed genes were not annotated. Further biological validation is therefore needed for these networks, using for example in vitro invalidation of genes. IS - Suppl 4 JF - BMC Proceedings SN - 1753-6561 TI - Gene network reconstruction from microarray data VL - 3 SP - S12 KW - biological_pathways KW - differentially_expressed_genes KW - network_topology KW - networks KW - pathways KW - reconstruction_software KW - regulatory_pathways KW - signaling_pathways AU - Jaffrezic, Florence AU - Klopp, Gwenola PY - 2009/// UR - http://dx.doi.org/10.1186/1753-6561-3-S4-S12 ER -