Literature DB >> 11465064

Phenotypic data in FlyBase.

R Drysdale1.   

Abstract

Phenotypic analysis combined with molecular genetics is a powerful tool for mapping gene function onto the genome. Phenotypic data are, by their nature, descriptive, and as varied as the range of mutant phenotypes that can be presented by the organism under study. This paper discusses the mechanisms FlyBase has implemented to systematise published phenotypic data about Drosophila, and provides an introduction to the query tools available for the mining of the data. Though FlyBase is specific to Drosophila, the issues faced in devising protocols for capturing, storing and reporting data are the same issues faced by any database with an interest in using phenotypic data to maximise the potential of genomic analysis.

Entities:  

Mesh:

Year:  2001        PMID: 11465064     DOI: 10.1093/bib/2.1.68

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  15 in total

1.  The FlyBase database of the Drosophila genome projects and community literature.

Authors: 
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

2.  Comparison of embryonic expression within multigene families using the FlyExpress discovery platform reveals more spatial than temporal divergence.

Authors:  Charlotte E Konikoff; Timothy L Karr; Michael McCutchan; Stuart J Newfeld; Sudhir Kumar
Journal:  Dev Dyn       Date:  2011-09-29       Impact factor: 3.780

3.  The FlyBase database of the Drosophila genome projects and community literature.

Authors: 
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

4.  Exploring FlyBase Data Using QuickSearch.

Authors:  Steven J Marygold; Giulia Antonazzo; Helen Attrill; Marta Costa; Madeline A Crosby; Gilberto Dos Santos; Joshua L Goodman; L Sian Gramates; Beverley B Matthews; Alix J Rey; Jim Thurmond
Journal:  Curr Protoc Bioinformatics       Date:  2016-12-08

5.  A gross anatomy ontology for hymenoptera.

Authors:  Matthew J Yoder; István Mikó; Katja C Seltmann; Matthew A Bertone; Andrew R Deans
Journal:  PLoS One       Date:  2010-12-29       Impact factor: 3.240

6.  Improving disease gene prioritization by comparing the semantic similarity of phenotypes in mice with those of human diseases.

Authors:  Anika Oellrich; Robert Hoehndorf; Georgios V Gkoutos; Dietrich Rebholz-Schuhmann
Journal:  PLoS One       Date:  2012-06-14       Impact factor: 3.240

7.  FlyBase: anatomical data, images and queries.

Authors:  Gary Grumbling; Victor Strelets
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

8.  Ontology-based cross-species integration and analysis of Saccharomyces cerevisiae phenotypes.

Authors:  Georgios V Gkoutos; Robert Hoehndorf
Journal:  J Biomed Semantics       Date:  2012-09-21

9.  Matching arthropod anatomy ontologies to the Hymenoptera Anatomy Ontology: results from a manual alignment.

Authors:  Matthew A Bertone; István Mikó; Matthew J Yoder; Katja C Seltmann; James P Balhoff; Andrew R Deans
Journal:  Database (Oxford)       Date:  2013-01-09       Impact factor: 3.451

10.  REDfly 2.0: an integrated database of cis-regulatory modules and transcription factor binding sites in Drosophila.

Authors:  Marc S Halfon; Steven M Gallo; Casey M Bergman
Journal:  Nucleic Acids Res       Date:  2007-11-26       Impact factor: 16.971

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.