Literature DB >> 19240125

Towards pharmacogenomics knowledge discovery with the semantic web.

Michel Dumontier1, Natalia Villanueva-Rosales.   

Abstract

Pharmacogenomics aims to understand pharmacological response with respect to genetic variation. Essential to the delivery of better health care is the use of pharmacogenomics knowledge to answer questions about therapeutic, pharmacological or genetic aspects. Several XML markup languages have been developed to capture pharmacogenomic and related information so as to facilitate data sharing. However, recent advances in semantic web technologies have presented exciting new opportunities for pharmacogenomics knowledge discovery by representing the information with machine understandable semantics. Progress in this area is illustrated with reference to the personalized medicine project that aims to facilitate pharmacogenomics knowledge discovery through intuitive knowledge capture and sophisticated question answering using automated reasoning over expressive ontologies.

Mesh:

Year:  2009        PMID: 19240125     DOI: 10.1093/bib/bbn056

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


  17 in total

1.  Using text to build semantic networks for pharmacogenomics.

Authors:  Adrien Coulet; Nigam H Shah; Yael Garten; Mark Musen; Russ B Altman
Journal:  J Biomed Inform       Date:  2010-08-17       Impact factor: 6.317

2.  Exploring the pharmacogenomics knowledge base (PharmGKB) for repositioning breast cancer drugs by leveraging Web ontology language (OWL) and cheminformatics approaches.

Authors:  Qian Zhu; Cui Tao; Feichen Shen; Christopher G Chute
Journal:  Pac Symp Biocomput       Date:  2014

3.  Learning from biomedical linked data to suggest valid pharmacogenes.

Authors:  Kevin Dalleau; Yassine Marzougui; Sébastien Da Silva; Patrice Ringot; Ndeye Coumba Ndiaye; Adrien Coulet
Journal:  J Biomed Semantics       Date:  2017-04-20

4.  Mining the pharmacogenomics literature--a survey of the state of the art.

Authors:  Udo Hahn; K Bretonnel Cohen; Yael Garten; Nigam H Shah
Journal:  Brief Bioinform       Date:  2012-07       Impact factor: 11.622

Review 5.  Semantically enabling pharmacogenomic data for the realization of personalized medicine.

Authors:  Matthias Samwald; Adrien Coulet; Iker Huerga; Robert L Powers; Joanne S Luciano; Robert R Freimuth; Frederick Whipple; Elgar Pichler; Eric Prud'hommeaux; Michel Dumontier; M Scott Marshall
Journal:  Pharmacogenomics       Date:  2012-01       Impact factor: 2.533

6.  The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside.

Authors:  Joanne S Luciano; Bosse Andersson; Colin Batchelor; Olivier Bodenreider; Tim Clark; Christine K Denney; Christopher Domarew; Thomas Gambet; Lee Harland; Anja Jentzsch; Vipul Kashyap; Peter Kos; Julia Kozlovsky; Timothy Lebo; Scott M Marshall; Jamie P. McCusker; Deborah L McGuinness; Chimezie Ogbuji; Elgar Pichler; Robert L Powers; Eric Prud'hommeaux; Matthias Samwald; Lynn Schriml; Peter J Tonellato; Patricia L Whetzel; Jun Zhao; Susie Stephens; Michel Dumontier
Journal:  J Biomed Semantics       Date:  2011-05-17

7.  VarioML framework for comprehensive variation data representation and exchange.

Authors:  Myles Byrne; Ivo Fac Fokkema; Owen Lancaster; Tomasz Adamusiak; Anni Ahonen-Bishopp; David Atlan; Christophe Béroud; Michael Cornell; Raymond Dalgleish; Andrew Devereau; George P Patrinos; Morris A Swertz; Peter Em Taschner; Gudmundur A Thorisson; Mauno Vihinen; Anthony J Brookes; Juha Muilu
Journal:  BMC Bioinformatics       Date:  2012-10-03       Impact factor: 3.169

8.  Improving integrative searching of systems chemical biology data using semantic annotation.

Authors:  Bin Chen; Ying Ding; David J Wild
Journal:  J Cheminform       Date:  2012-03-08       Impact factor: 5.514

9.  HyQue: evaluating hypotheses using Semantic Web technologies.

Authors:  Alison Callahan; Michel Dumontier; Nigam H Shah
Journal:  J Biomed Semantics       Date:  2011-05-17

10.  Semantic enrichment of longitudinal clinical study data using the CDISC standards and the semantic statistics vocabularies.

Authors:  Hugo Leroux; Laurent Lefort
Journal:  J Biomed Semantics       Date:  2015-04-09
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.