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Empowering pharmacoinformatics by linked life science data
With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or P...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385323/ https://www.ncbi.nlm.nih.gov/pubmed/27830428 http://dx.doi.org/10.1007/s10822-016-9990-4 |
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author | Goldmann, Daria Zdrazil, Barbara Digles, Daniela Ecker, Gerhard F. |
author_facet | Goldmann, Daria Zdrazil, Barbara Digles, Daniela Ecker, Gerhard F. |
author_sort | Goldmann, Daria |
collection | PubMed |
description | With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-016-9990-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5385323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-53853232017-04-24 Empowering pharmacoinformatics by linked life science data Goldmann, Daria Zdrazil, Barbara Digles, Daniela Ecker, Gerhard F. J Comput Aided Mol Des Article With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-016-9990-4) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-11-09 2017 /pmc/articles/PMC5385323/ /pubmed/27830428 http://dx.doi.org/10.1007/s10822-016-9990-4 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Goldmann, Daria Zdrazil, Barbara Digles, Daniela Ecker, Gerhard F. Empowering pharmacoinformatics by linked life science data |
title | Empowering pharmacoinformatics by linked life science data |
title_full | Empowering pharmacoinformatics by linked life science data |
title_fullStr | Empowering pharmacoinformatics by linked life science data |
title_full_unstemmed | Empowering pharmacoinformatics by linked life science data |
title_short | Empowering pharmacoinformatics by linked life science data |
title_sort | empowering pharmacoinformatics by linked life science data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385323/ https://www.ncbi.nlm.nih.gov/pubmed/27830428 http://dx.doi.org/10.1007/s10822-016-9990-4 |
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