Literature DB >> 23149630

Linking genome annotation projects with genetic disorders using ontologies.

María del Carmen Legaz-García1, José Antonio Miñarro-Giménez, Marisa Madrid, Marcos Menárguez-Tortosa, Santiago Torres Martínez, Jesualdo Tomás Fernández-Breis.   

Abstract

Genome sequencing projects generate vast amounts of data of a wide variety of types and complexities, and at a growing pace. Traditionally, the annotation of such sequences was difficult to share with other researchers. Despite the fact that this has improved with the development and application of biological ontologies, such annotation efforts remain isolated since the amount of information that can be used from other annotation projects is limited. In addition to this, they do not benefit from the translational information available for the genomic sequences. In this paper, we describe a system that supports genome annotation processes by providing useful information about orthologous genes and the genetic disorders which can be associated with a gene identified in a sequence. The seamless integration of such data will be facilitated by an ontological infrastructure which, following best practices in ontology engineering, will reuse existing biological ontologies like Sequence Ontology or Ontological Gene Orthology.

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Year:  2012        PMID: 23149630     DOI: 10.1007/s10916-012-9890-7

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  21 in total

1.  Letter to the editor: SeqXML and OrthoXML: standards for sequence and orthology information.

Authors:  Thomas Schmitt; David N Messina; Fabian Schreiber; Erik L L Sonnhammer
Journal:  Brief Bioinform       Date:  2011-06-11       Impact factor: 11.622

2.  Semantic integration of information about orthologs and diseases: the OGO system.

Authors:  Jose Antonio Miñarro-Gimenez; Mikel Egaña Aranguren; Rodrigo Martínez Béjar; Jesualdo Tomás Fernández-Breis; Marisa Madrid
Journal:  J Biomed Inform       Date:  2011-08-16       Impact factor: 6.317

3.  The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology.

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Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

4.  The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease.

Authors:  Peter N Robinson; Sebastian Köhler; Sebastian Bauer; Dominik Seelow; Denise Horn; Stefan Mundlos
Journal:  Am J Hum Genet       Date:  2008-10-23       Impact factor: 11.025

5.  The Drosophila Mst ortholog, hippo, restricts growth and cell proliferation and promotes apoptosis.

Authors:  Kieran F Harvey; Cathie M Pfleger; Iswar K Hariharan
Journal:  Cell       Date:  2003-08-22       Impact factor: 41.582

6.  An ontology for cell types.

Authors:  Jonathan Bard; Seung Y Rhee; Michael Ashburner
Journal:  Genome Biol       Date:  2005-01-14       Impact factor: 13.583

7.  SOBA: sequence ontology bioinformatics analysis.

Authors:  Barry Moore; Guozhen Fan; Karen Eilbeck
Journal:  Nucleic Acids Res       Date:  2010-05-21       Impact factor: 16.971

8.  OGO: an ontological approach for integrating knowledge about orthology.

Authors:  Jose Antonio Miñarro-Gimenez; Marisa Madrid; Jesualdo Tomas Fernandez-Breis
Journal:  BMC Bioinformatics       Date:  2009-10-01       Impact factor: 3.307

9.  POCUS: mining genomic sequence annotation to predict disease genes.

Authors:  Frances S Turner; Daniel R Clutterbuck; Colin A M Semple
Journal:  Genome Biol       Date:  2003-10-10       Impact factor: 13.583

10.  The COG database: an updated version includes eukaryotes.

Authors:  Roman L Tatusov; Natalie D Fedorova; John D Jackson; Aviva R Jacobs; Boris Kiryutin; Eugene V Koonin; Dmitri M Krylov; Raja Mazumder; Sergei L Mekhedov; Anastasia N Nikolskaya; B Sridhar Rao; Sergei Smirnov; Alexander V Sverdlov; Sona Vasudevan; Yuri I Wolf; Jodie J Yin; Darren A Natale
Journal:  BMC Bioinformatics       Date:  2003-09-11       Impact factor: 3.169

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  1 in total

1.  OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

Authors:  Agne Antanaviciute; Christopher M Watson; Sally M Harrison; Carolina Lascelles; Laura Crinnion; Alexander F Markham; David T Bonthron; Ian M Carr
Journal:  Bioinformatics       Date:  2015-08-12       Impact factor: 6.937

  1 in total

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