Microarray data analysis and mining approaches

@article{citeulike:2316815, abstract = {Microarray based transcription profiling is now a consolidated methodology and has widespread use in areas such as pharmacogenomics, diagnostics and drug target identification. Large-scale microarray studies are also becoming crucial to a new way of conceiving experimental biology. A main issue in microarray transcription profiling is data analysis and mining. When microarrays became a methodology of general use, considerable effort was made to produce algorithms and methods for the identification of differentially expressed genes. More recently, the focus has switched to algorithms and database development for microarray data mining. Furthermore, the evolution of microarray technology is allowing researchers to grasp the regulative nature of transcription, integrating basic expression analysis with mRNA characteristics, i.e. exon-based arrays, and with DNA characteristics, i.e. comparative genomic hybridization, single nucleotide polymorphism, tiling and promoter structure. In this article, we will review approaches used to detect differentially expressed genes and to link differential expression to specific biological functions. 10.1093/bfgp/elm034}, author = {Cordero, Francesca and Botta, Marco and Calogero, Raffaele A. }, citeulike-article-id = {2316815}, doi = {http://dx.doi.org/10.1093/bfgp/elm034}, journal = {Brief Funct Genomic Proteomic}, keywords = {biomarkers, microarray}, month = {January}, pages = {elm034+}, posted-at = {2008-05-16 22:21:51}, priority = {0}, title = {Microarray data analysis and mining approaches}, url = {http://dx.doi.org/10.1093/bfgp/elm034}, year = {2008} }

TY - JOUR ID - citeulike:2316815 L3 - citeulike-article-id:2316815 TI - Microarray data analysis and mining approaches JF - Brief Funct Genomic Proteomic SP - elm034 N2 - Microarray based transcription profiling is now a consolidated methodology and has widespread use in areas such as pharmacogenomics, diagnostics and drug target identification. Large-scale microarray studies are also becoming crucial to a new way of conceiving experimental biology. A main issue in microarray transcription profiling is data analysis and mining. When microarrays became a methodology of general use, considerable effort was made to produce algorithms and methods for the identification of differentially expressed genes. More recently, the focus has switched to algorithms and database development for microarray data mining. Furthermore, the evolution of microarray technology is allowing researchers to grasp the regulative nature of transcription, integrating basic expression analysis with mRNA characteristics, i.e. exon-based arrays, and with DNA characteristics, i.e. comparative genomic hybridization, single nucleotide polymorphism, tiling and promoter structure. In this article, we will review approaches used to detect differentially expressed genes and to link differential expression to specific biological functions. 10.1093/bfgp/elm034 KW - biomarkers KW - microarray AU - Cordero, Francesca AU - Botta, Marco AU - Calogero, Raffaele PY - 2008/01/22/ UR - http://dx.doi.org/10.1093/bfgp/elm034 ER -