Literature DB >> 22222943

Systems chemical biology and the Semantic Web: what they mean for the future of drug discovery research.

David J Wild1, Ying Ding, Amit P Sheth, Lee Harland, Eric M Gifford, Michael S Lajiness.   

Abstract

Systems chemical biology, the integration of chemistry, biology and computation to generate understanding about the way small molecules affect biological systems as a whole, as well as related fields such as chemogenomics, are central to emerging new paradigms of drug discovery such as drug repurposing and personalized medicine. Recent Semantic Web technologies such as RDF and SPARQL are technical enablers of systems chemical biology, facilitating the deployment of advanced algorithms for searching and mining large integrated datasets. In this paper, we aim to demonstrate how these technologies together can change the way that drug discovery is accomplished.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 22222943     DOI: 10.1016/j.drudis.2011.12.019

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  18 in total

Review 1.  Systems biology for molecular life sciences and its impact in biomedicine.

Authors:  Miguel Ángel Medina
Journal:  Cell Mol Life Sci       Date:  2012-08-19       Impact factor: 9.261

2.  The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

Authors:  Santiago Vilar; George Hripcsak
Journal:  Brief Bioinform       Date:  2017-07-01       Impact factor: 11.622

3.  GPCR ontology: development and application of a G protein-coupled receptor pharmacology knowledge framework.

Authors:  Magdalena J Przydzial; Barun Bhhatarai; Amar Koleti; Uma Vempati; Stephan C Schürer
Journal:  Bioinformatics       Date:  2013-09-29       Impact factor: 6.937

4.  A semantics, energy-based approach to automate biomodel composition.

Authors:  Niloofar Shahidi; Michael Pan; Kenneth Tran; Edmund J Crampin; David P Nickerson
Journal:  PLoS One       Date:  2022-06-03       Impact factor: 3.752

Review 5.  Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.

Authors:  Yen Sia Low; Alexander Yeugenyevich Sedykh; Ivan Rusyn; Alexander Tropsha
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

6.  PharmaTrek: A Semantic Web Explorer for Open Innovation in Multitarget Drug Discovery.

Authors:  Maria C Carrascosa; Oriol L Massaguer; Jordi Mestres
Journal:  Mol Inform       Date:  2012-08-07       Impact factor: 3.353

7.  Profiling structured product labeling with NDF-RT and RxNorm.

Authors:  Qian Zhu; Guoqian Jiang; Christopher G Chute
Journal:  J Biomed Semantics       Date:  2012-12-20

8.  ChemProt-2.0: visual navigation in a disease chemical biology database.

Authors:  Sonny Kim Kjærulff; Louis Wich; Jens Kringelum; Ulrik P Jacobsen; Irene Kouskoumvekaki; Karine Audouze; Ole Lund; Søren Brunak; Tudor I Oprea; Olivier Taboureau
Journal:  Nucleic Acids Res       Date:  2012-11-26       Impact factor: 16.971

9.  Assessing drug target association using semantic linked data.

Authors:  Bin Chen; Ying Ding; David J Wild
Journal:  PLoS Comput Biol       Date:  2012-07-05       Impact factor: 4.475

10.  Optimizing drug-target interaction prediction based on random walk on heterogeneous networks.

Authors:  Abhik Seal; Yong-Yeol Ahn; David J Wild
Journal:  J Cheminform       Date:  2015-08-19       Impact factor: 5.514

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