Microarray analysis of gene expression: considerations in data mining and statistical treatment Export

@article{citeulike:2823358, abstract = {DNA microarray represents a powerful tool in biomedical discoveries. Harnessing the potential of this technology depends on the development and appropriate use of data mining and statistical tools. Significant current advances have made microarray data mining more versatile. Researchers are no longer limited to default choices that generate suboptimal results. Conflicting results in repeated experiments can be resolved through attention to the statistical details. In the current dynamic environment, there are many choices and potential pitfalls for researchers who intend to incorporate microarrays as a research tool. This review is intended to provide a simple framework to understand the choices and identify the pitfalls. Specifically, this review article discusses the choice of microarray platform, preprocessing raw data, differential expression and validation, clustering, annotation and functional characterization of genes, and pathway construction in light of emergent concepts and tools. 10.1152/physiolgenomics.00314.2004}, address = {Davis Heart and Lung Research Institute, Department of Surgery, The Ohio State University, Columbus, Ohio, USA.}, author = {Verducci, Joseph S. and Melfi, Vincent F. and Lin, Shili and Wang, Zailong and Roy, Sashwati and Sen, Chandan K.}, citeulike-article-id = {2823358}, citeulike-linkout-0 = {http://dx.doi.org/10.1152/physiolgenomics.00314.2004}, citeulike-linkout-1 = {http://physiolgenomics.physiology.org/content/25/3/355.abstract}, citeulike-linkout-2 = {http://physiolgenomics.physiology.org/content/25/3/355.full.pdf}, citeulike-linkout-3 = {http://physiolgenomics.physiology.org/cgi/content/abstract/25/3/355}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/16554544}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=16554544}, day = {16}, doi = {10.1152/physiolgenomics.00314.2004}, issn = {1531-2267}, journal = {Physiol. Genomics}, keywords = {analysis, data\_mining, microarray, review, statistics}, month = {May}, number = {3}, pages = {355--363}, posted-at = {2008-10-14 11:11:33}, priority = {2}, title = {Microarray analysis of gene expression: considerations in data mining and statistical treatment}, url = {http://dx.doi.org/10.1152/physiolgenomics.00314.2004}, volume = {25}, year = {2006} }

TY - JOUR ID - citeulike:2823358 L3 - citeulike-article-id:2823358 N2 - DNA microarray represents a powerful tool in biomedical discoveries. Harnessing the potential of this technology depends on the development and appropriate use of data mining and statistical tools. Significant current advances have made microarray data mining more versatile. Researchers are no longer limited to default choices that generate suboptimal results. Conflicting results in repeated experiments can be resolved through attention to the statistical details. In the current dynamic environment, there are many choices and potential pitfalls for researchers who intend to incorporate microarrays as a research tool. This review is intended to provide a simple framework to understand the choices and identify the pitfalls. Specifically, this review article discusses the choice of microarray platform, preprocessing raw data, differential expression and validation, clustering, annotation and functional characterization of genes, and pathway construction in light of emergent concepts and tools. 10.1152/physiolgenomics.00314.2004 IS - 3 JF - Physiol. Genomics SN - 1531-2267 AD - Davis Heart and Lung Research Institute, Department of Surgery, The Ohio State University, Columbus, Ohio, USA. EP - 363 TI - Microarray analysis of gene expression: considerations in data mining and statistical treatment VL - 25 SP - 355 KW - analysis KW - data_mining KW - microarray KW - review KW - statistics AU - Verducci, Joseph AU - Melfi, Vincent AU - Lin, Shili AU - Wang, Zailong AU - Roy, Sashwati AU - Sen, Chandan PY - 2006/05/16/ UR - http://dx.doi.org/10.1152/physiolgenomics.00314.2004 ER -