Literature DB >> 17675869

GOing from functional genomics to biological significance.

F M McCarthy1, S M Bridges, S C Burgess.   

Abstract

The chicken genome is sequenced and this, together with microarray and other functional genomics technologies, makes post-genomic research possible in the chicken. At this time, however, such research is hindered by a lack of genomic structural and functional annotations. Bio-ontologies have been developed for different annotation requirements, as well as to facilitate data sharing and computational analysis, but these are not yet optimally utilized in the chicken. Here we discuss genomic annotation and bio-ontologies. We focus specifically on the Gene Ontology (GO), chicken GO annotations and how these can facilitate functional genomics in the chicken. The GO is the most developed and widely used bio-ontology. It is the de facto standard for functional annotation. Despite its critical importance in analyzing microarray and other functional genomics data, relatively few chicken gene products have any GO annotation. When these are available, the average quality of chicken gene products annotations (defined using evidence code weight and annotation depth) is much less than in mouse. Moreover, tools allowing chicken researchers to easily and rapidly use the GO are either lacking or hard to use. To address all of these problems we developed ChickGO and AgBase. Chicken GO annotations are provided by complementary work at MSU-AgBase and EBI-GOA. The GO tools pipeline at AgBase uses GO to derive functional and biological significance from microarray and other functional genomics data. Not only will improved genomic annotation and tools to use these annotations benefit the chicken research community but they will also facilitate research in other avian species and comparative genomics. Copyright 2007 S. Karger AG, Basel.

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Mesh:

Year:  2007        PMID: 17675869     DOI: 10.1159/000103189

Source DB:  PubMed          Journal:  Cytogenet Genome Res        ISSN: 1424-8581            Impact factor:   1.636


  6 in total

1.  Global liver proteomics of rats exposed for 5 days to phenobarbital identifies changes associated with cancer and with CYP metabolism.

Authors:  Mary B Dail; L Allen Shack; Janice E Chambers; Shane C Burgess
Journal:  Toxicol Sci       Date:  2008-09-16       Impact factor: 4.849

2.  Gene ontology function prediction in mollicutes using protein-protein association networks.

Authors:  Antonio Gómez; Juan Cedano; Isaac Amela; Antoni Planas; Jaume Piñol; Enrique Querol
Journal:  BMC Syst Biol       Date:  2011-04-12

3.  Ultrasonic incisions produce less inflammatory mediator response during early healing than electrosurgical incisions.

Authors:  Bindu Nanduri; Ken Pendarvis; Leslie A Shack; Ranjit Kumar; Jeffrey W Clymer; Donna L Korvick; Shane C Burgess
Journal:  PLoS One       Date:  2013-09-18       Impact factor: 3.240

4.  Genotype-dependent tumor regression in Marek's disease mediated at the level of tumor immunity.

Authors:  Shyamesh Kumar; Joram J Buza; Shane C Burgess
Journal:  Cancer Microenviron       Date:  2009-03-18

5.  Structural and functional-annotation of an equine whole genome oligoarray.

Authors:  Lauren A Bright; Shane C Burgess; Bhanu Chowdhary; Cyprianna E Swiderski; Fiona M McCarthy
Journal:  BMC Bioinformatics       Date:  2009-10-08       Impact factor: 3.169

6.  Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology.

Authors:  David P Hill; Nico Adams; Mike Bada; Colin Batchelor; Tanya Z Berardini; Heiko Dietze; Harold J Drabkin; Marcus Ennis; Rebecca E Foulger; Midori A Harris; Janna Hastings; Namrata S Kale; Paula de Matos; Christopher J Mungall; Gareth Owen; Paola Roncaglia; Christoph Steinbeck; Steve Turner; Jane Lomax
Journal:  BMC Genomics       Date:  2013-07-29       Impact factor: 3.969

  6 in total

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