Gene Ontology annotation quality analysis in model eukaryotes. Export

@article{citeulike:2249141, abstract = {Functional analysis using the Gene Ontology (GO) is crucial for array analysis, but it is often difficult for researchers to assess the amount and quality of GO annotations associated with different sets of gene products. In many cases the source of the GO annotations and the date the GO annotations were last updated is not apparent, further complicating a researchers' ability to assess the quality of the GO data provided. Moreover, GO biocurators need to ensure that the GO quality is maintained and optimal for the functional processes that are most relevant for their research community. We report the GO Annotation Quality (GAQ) score, a quantitative measure of GO quality that includes breadth of GO annotation, the level of detail of annotation and the type of evidence used to make the annotation. As a case study, we apply the GAQ scoring method to a set of diverse eukaryotes and demonstrate how the GAQ score can be used to track changes in GO annotations over time and to assess the quality of GO annotations available for specific biological processes. The GAQ score also allows researchers to quantitatively assess the functional data available for their experimental systems (arrays or databases).}, address = {Department of Basic Sciences, Department of Computer Science and Engineering, Institute of Digital Biology, Mississippi Agricultural and Forestry Experiment Station and Life Sciences and Biotechnology Institute, Mississippi State University, Mississippi 39762, USA.}, author = {Buza, Teresia J J. and McCarthy, Fiona M M. and Wang, Nan and Bridges, Susan M M. and Burgess, Shane C C.}, citeulike-article-id = {2249141}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/18187504}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=18187504}, day = {10}, issn = {1362-4962}, journal = {Nucleic Acids Res}, keywords = {annotation, go}, month = {January}, posted-at = {2008-10-14 14:29:18}, priority = {2}, title = {Gene Ontology annotation quality analysis in model eukaryotes.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/18187504}, year = {2008} }

TY - JOUR ID - citeulike:2249141 L3 - citeulike-article-id:2249141 N2 - Functional analysis using the Gene Ontology (GO) is crucial for array analysis, but it is often difficult for researchers to assess the amount and quality of GO annotations associated with different sets of gene products. In many cases the source of the GO annotations and the date the GO annotations were last updated is not apparent, further complicating a researchers' ability to assess the quality of the GO data provided. Moreover, GO biocurators need to ensure that the GO quality is maintained and optimal for the functional processes that are most relevant for their research community. We report the GO Annotation Quality (GAQ) score, a quantitative measure of GO quality that includes breadth of GO annotation, the level of detail of annotation and the type of evidence used to make the annotation. As a case study, we apply the GAQ scoring method to a set of diverse eukaryotes and demonstrate how the GAQ score can be used to track changes in GO annotations over time and to assess the quality of GO annotations available for specific biological processes. The GAQ score also allows researchers to quantitatively assess the functional data available for their experimental systems (arrays or databases). JF - Nucleic Acids Res SN - 1362-4962 AD - Department of Basic Sciences, Department of Computer Science and Engineering, Institute of Digital Biology, Mississippi Agricultural and Forestry Experiment Station and Life Sciences and Biotechnology Institute, Mississippi State University, Mississippi 39762, USA. TI - Gene Ontology annotation quality analysis in model eukaryotes. KW - annotation KW - go AU - Buza, Teresia J AU - McCarthy, Fiona M AU - Wang, Nan AU - Bridges, Susan M AU - Burgess, Shane C PY - 2008/01/10/ UR - http://view.ncbi.nlm.nih.gov/pubmed/18187504 ER -