Literature DB >> 10886027

Algorithms for mutant sorting: the need for phenotype vocabularies.

J T Eppig1.   

Abstract

For effectively annotated phenotypes for mouse, a number of detailed phenotypic classification systems are needed. The rapidly increasing number of phenotypically described characteristics of both normal and mutant mice are providing a rich data set for comparison and analysis. However, we cannot rely on text descriptions that are subject to the word-usage style of the writer if we are to do large-scale comparative analysis of traits and diseases. The rationale for developing vocabularies and examples of several vocabularies being developed are described. Finally, the critical nature of community participation in both building and applying phenotype vocabularies is discussed.

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Year:  2000        PMID: 10886027     DOI: 10.1007/s003350010111

Source DB:  PubMed          Journal:  Mamm Genome        ISSN: 0938-8990            Impact factor:   2.957


  4 in total

Review 1.  Surviving in a sea of data: a survey of plant genome data resources and issues in building data management systems.

Authors:  Leonore Reiser; Lukas A Mueller; Seung Yon Rhee
Journal:  Plant Mol Biol       Date:  2002-01       Impact factor: 4.076

2.  The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information.

Authors:  Cynthia L Smith; Carroll-Ann W Goldsmith; Janan T Eppig
Journal:  Genome Biol       Date:  2004-12-15       Impact factor: 13.583

3.  Novel skin phenotypes revealed by a genome-wide mouse reverse genetic screen.

Authors:  Kifayathullah Liakath-Ali; Valerie E Vancollie; Emma Heath; Damian P Smedley; Jeanne Estabel; David Sunter; Tia Ditommaso; Jacqueline K White; Ramiro Ramirez-Solis; Ian Smyth; Karen P Steel; Fiona M Watt
Journal:  Nat Commun       Date:  2014-04-11       Impact factor: 14.919

4.  The anatomy of phenotype ontologies: principles, properties and applications.

Authors:  Georgios V Gkoutos; Paul N Schofield; Robert Hoehndorf
Journal:  Brief Bioinform       Date:  2018-09-28       Impact factor: 11.622

  4 in total

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