Literature DB >> 19921742

Representing ontogeny through ontology: a developmental biologist's guide to the gene ontology.

David P Hill1, Tanya Z Berardini, Douglas G Howe, Kimberly M Van Auken.   

Abstract

Developmental biology, like many other areas of biology, has undergone a dramatic shift in the perspective from which developmental processes are viewed. Instead of focusing on the actions of a handful of genes or functional RNAs, we now consider the interactions of large functional gene networks and study how these complex systems orchestrate the unfolding of an organism, from gametes to adult. Developmental biologists are beginning to realize that understanding ontogeny on this scale requires the utilization of computational methods to capture, store and represent the knowledge we have about the underlying processes. Here we review the use of the Gene Ontology (GO) to study developmental biology. We describe the organization and structure of the GO and illustrate some of the ways we use it to capture the current understanding of many common developmental processes. We also discuss ways in which gene product annotations using the GO have been used to ask and answer developmental questions in a variety of model developmental systems. We provide suggestions as to how the GO might be used in more powerful ways to address questions about development. Our goal is to provide developmental biologists with enough background about the GO that they can begin to think about how they might use the ontology efficiently and in the most powerful ways possible. Copyright 2009 Wiley-Liss, Inc.

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Year:  2010        PMID: 19921742      PMCID: PMC2830379          DOI: 10.1002/mrd.21130

Source DB:  PubMed          Journal:  Mol Reprod Dev        ISSN: 1040-452X            Impact factor:   2.609


  84 in total

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

2.  Applications of InterPro in protein annotation and genome analysis.

Authors:  Margaret Biswas; John F O'Rourke; Evelyn Camon; Gill Fraser; Alexander Kanapin; Youla Karavidopoulou; Paul Kersey; Evgenia Kriventseva; Virginie Mittard; Nicola Mulder; Isabelle Phan; Florence Servant; Rolf Apweiler
Journal:  Brief Bioinform       Date:  2002-09       Impact factor: 11.622

3.  Gene expression profiling during the embryonic development of mouse brain using an oligonucleotide-based microarray system.

Authors:  Tohru Matsuki; Gen Hori; Teiichi Furuichi
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4.  Alterations in gene expression in the testis of angiotensin-(1-7)-receptor Mas-deficient mice.

Authors:  Ping Xu; Robson A S Santos; Michael Bader; Natalia Alenina
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5.  Genome-wide germline-enriched and sex-biased expression profiles in Caenorhabditis elegans.

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Journal:  Development       Date:  2003-12-10       Impact factor: 6.868

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Journal:  Differentiation       Date:  2003-01       Impact factor: 3.880

7.  Transcriptome analyses show changes in gene expression to accompany pollen germination and tube growth in Arabidopsis.

Authors:  Yi Wang; Wen-Zheng Zhang; Lian-Fen Song; Jun-Jie Zou; Zhen Su; Wei-Hua Wu
Journal:  Plant Physiol       Date:  2008-09-05       Impact factor: 8.340

8.  GRP94 is essential for mesoderm induction and muscle development because it regulates insulin-like growth factor secretion.

Authors:  Sherry Wanderling; Birgitte B Simen; Olga Ostrovsky; Noreen T Ahmed; Shawn M Vogen; Tali Gidalevitz; Yair Argon
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10.  The Adult Mouse Anatomical Dictionary: a tool for annotating and integrating data.

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  7 in total

1.  The representation of heart development in the gene ontology.

Authors:  Varsha K Khodiyar; David P Hill; Doug Howe; Tanya Z Berardini; Susan Tweedie; Philippa J Talmud; Ross Breckenridge; Shoumo Bhattarcharya; Paul Riley; Peter Scambler; Ruth C Lovering
Journal:  Dev Biol       Date:  2011-03-17       Impact factor: 3.582

2.  Overview of the gene ontology task at BioCreative IV.

Authors:  Yuqing Mao; Kimberly Van Auken; Donghui Li; Cecilia N Arighi; Peter McQuilton; G Thomas Hayman; Susan Tweedie; Mary L Schaeffer; Stanley J F Laulederkind; Shur-Jen Wang; Julien Gobeill; Patrick Ruch; Anh Tuan Luu; Jung-Jae Kim; Jung-Hsien Chiang; Yu-De Chen; Chia-Jung Yang; Hongfang Liu; Dongqing Zhu; Yanpeng Li; Hong Yu; Ehsan Emadzadeh; Graciela Gonzalez; Jian-Ming Chen; Hong-Jie Dai; Zhiyong Lu
Journal:  Database (Oxford)       Date:  2014-08-25       Impact factor: 3.451

3.  Cell-type-specific predictive network yields novel insights into mouse embryonic stem cell self-renewal and cell fate.

Authors:  Karen G Dowell; Allen K Simons; Zack Z Wang; Kyuson Yun; Matthew A Hibbs
Journal:  PLoS One       Date:  2013-02-28       Impact factor: 3.240

4.  A multilayer ontology of instruments for neurological, behavioral and cognitive assessments.

Authors:  Bénédicte Batrancourt; Michel Dojat; Bernard Gibaud; Gilles Kassel
Journal:  Neuroinformatics       Date:  2015-01

5.  Ontology-based representation and analysis of host-Brucella interactions.

Authors:  Yu Lin; Zuoshuang Xiang; Yongqun He
Journal:  J Biomed Semantics       Date:  2015-10-05

6.  BC4GO: a full-text corpus for the BioCreative IV GO task.

Authors:  Kimberly Van Auken; Mary L Schaeffer; Peter McQuilton; Stanley J F Laulederkind; Donghui Li; Shur-Jen Wang; G Thomas Hayman; Susan Tweedie; Cecilia N Arighi; James Done; Hans-Michael Müller; Paul W Sternberg; Yuqing Mao; Chih-Hsuan Wei; Zhiyong Lu
Journal:  Database (Oxford)       Date:  2014-07-28       Impact factor: 3.451

7.  Representation of anatomy in online atlases and databases: a survey and collection of patterns for interface design.

Authors:  Melissa D Clarkson
Journal:  BMC Dev Biol       Date:  2016-05-21       Impact factor: 1.978

  7 in total

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