Linking the genes: inferring quantitative gene networks from microarray data. Export

@article{citeulike:1634691, abstract = {Modern microarray technology is capable of providing data about the expression of thousands of genes, and even of whole genomes. An important question is how this technology can be used most effectively to unravel the workings of cellular machinery. Here, we propose a method to infer genetic networks on the basis of data from appropriately designed microarray experiments. In addition to identifying the genes that affect a specific other gene directly, this method also estimates the strength of such effects. We will discuss both the experimental setup and the theoretical background.}, address = {Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061, USA.}, author = {de la Fuente, A. and Brazhnik, P. and Mendes, P.}, citeulike-article-id = {1634691}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/12142007}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=12142007}, issn = {0168-9525}, journal = {Trends Genet}, keywords = {network}, month = {August}, number = {8}, pages = {395--398}, posted-at = {2007-09-08 19:07:00}, priority = {4}, title = {Linking the genes: inferring quantitative gene networks from microarray data.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/12142007}, volume = {18}, year = {2002} }

TY - JOUR ID - citeulike:1634691 L3 - citeulike-article-id:1634691 N2 - Modern microarray technology is capable of providing data about the expression of thousands of genes, and even of whole genomes. An important question is how this technology can be used most effectively to unravel the workings of cellular machinery. Here, we propose a method to infer genetic networks on the basis of data from appropriately designed microarray experiments. In addition to identifying the genes that affect a specific other gene directly, this method also estimates the strength of such effects. We will discuss both the experimental setup and the theoretical background. IS - 8 JF - Trends Genet SN - 0168-9525 AD - Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061, USA. EP - 398 TI - Linking the genes: inferring quantitative gene networks from microarray data. VL - 18 SP - 395 KW - network AU - de la Fuente, A AU - Brazhnik, P AU - Mendes, P PY - 2002/08// UR - http://view.ncbi.nlm.nih.gov/pubmed/12142007 ER -