Literature DB >> 15688072

Data integration: challenges for drug discovery.

David B Searls1.   

Abstract

The effective integration of data and knowledge from many disparate sources will be crucial to future drug discovery. Data integration is a key element of conducting scientific investigations with modern platform technologies, managing increasingly complex discovery portfolios and processes, and fully realizing economies of scale in large enterprises. However, viewing data integration as simply an 'IT problem' underestimates the novel and serious scientific and management challenges it embodies - challenges that could require significant methodological and even cultural changes in our approach to data.

Mesh:

Year:  2005        PMID: 15688072     DOI: 10.1038/nrd1608

Source DB:  PubMed          Journal:  Nat Rev Drug Discov        ISSN: 1474-1776            Impact factor:   84.694


  38 in total

1.  Supporting retrieval of diverse biomedical data using evidence-aware queries.

Authors:  Eithon Cadag; Peter Tarczy-Hornoch
Journal:  J Biomed Inform       Date:  2010-07-17       Impact factor: 6.317

Review 2.  Bioinformatics and cancer: an essential alliance.

Authors:  Joaquín Dopazo
Journal:  Clin Transl Oncol       Date:  2006-06       Impact factor: 3.405

3.  Combining evidence of preferential gene-tissue relationships from multiple sources.

Authors:  Jing Guo; Mårten Hammar; Lisa Oberg; Shanmukha S Padmanabhuni; Marcus Bjäreland; Daniel Dalevi
Journal:  PLoS One       Date:  2013-08-12       Impact factor: 3.240

4.  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

5.  PICan: An integromics framework for dynamic cancer biomarker discovery.

Authors:  Darragh G McArt; Jaine K Blayney; David P Boyle; Gareth W Irwin; Michael Moran; Ryan A Hutchinson; Peter Bankhead; Declan Kieran; Yinhai Wang; Philip D Dunne; Richard D Kennedy; Paul B Mullan; D Paul Harkin; Mark A Catherwood; Jacqueline A James; Manuel Salto-Tellez; Peter W Hamilton
Journal:  Mol Oncol       Date:  2015-03-04       Impact factor: 6.603

6.  Digital images are data: and should be treated as such.

Authors:  Douglas W Cromey
Journal:  Methods Mol Biol       Date:  2013

Review 7.  Machine learning in chemoinformatics and drug discovery.

Authors:  Yu-Chen Lo; Stefano E Rensi; Wen Torng; Russ B Altman
Journal:  Drug Discov Today       Date:  2018-05-08       Impact factor: 7.851

8.  Drug off-target effects predicted using structural analysis in the context of a metabolic network model.

Authors:  Roger L Chang; Li Xie; Lei Xie; Philip E Bourne; Bernhard Ø Palsson
Journal:  PLoS Comput Biol       Date:  2010-09-23       Impact factor: 4.475

9.  Detection of mammalian virulence determinants in highly pathogenic avian influenza H5N1 viruses: multivariate analysis of published data.

Authors:  S J Lycett; M J Ward; F I Lewis; A F Y Poon; S L Kosakovsky Pond; A J Leigh Brown
Journal:  J Virol       Date:  2009-07-22       Impact factor: 5.103

10.  Ontologies for bioinformatics.

Authors:  Nadine Schuurman; Agnieszka Leszczynski
Journal:  Bioinform Biol Insights       Date:  2008-03-12
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