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Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited

The ‘big data’ concept plays an increasingly important role in many scientific fields. Big data involves more than unprecedentedly large volumes of data that become available. Different criteria characterizing big data must be carefully considered in computational data mining, as we discuss herein f...

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Detalles Bibliográficos
Autores principales: Hu, Ye, Bajorath, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Science Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5481856/
https://www.ncbi.nlm.nih.gov/pubmed/28670471
http://dx.doi.org/10.4155/fsoa-2017-0001
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author Hu, Ye
Bajorath, Jürgen
author_facet Hu, Ye
Bajorath, Jürgen
author_sort Hu, Ye
collection PubMed
description The ‘big data’ concept plays an increasingly important role in many scientific fields. Big data involves more than unprecedentedly large volumes of data that become available. Different criteria characterizing big data must be carefully considered in computational data mining, as we discuss herein focusing on medicinal chemistry. This is a scientific discipline where big data is beginning to emerge and provide new opportunities. For example, the ability of many drugs to specifically interact with multiple targets, termed promiscuity, forms the molecular basis of polypharmacology, a hot topic in drug discovery. Compound promiscuity analysis is an area that is much influenced by big data phenomena. Different results are obtained depending on chosen data selection and confidence criteria, as we also demonstrate.
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spelling pubmed-54818562017-06-30 Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited Hu, Ye Bajorath, Jürgen Future Sci OA Perspective The ‘big data’ concept plays an increasingly important role in many scientific fields. Big data involves more than unprecedentedly large volumes of data that become available. Different criteria characterizing big data must be carefully considered in computational data mining, as we discuss herein focusing on medicinal chemistry. This is a scientific discipline where big data is beginning to emerge and provide new opportunities. For example, the ability of many drugs to specifically interact with multiple targets, termed promiscuity, forms the molecular basis of polypharmacology, a hot topic in drug discovery. Compound promiscuity analysis is an area that is much influenced by big data phenomena. Different results are obtained depending on chosen data selection and confidence criteria, as we also demonstrate. Future Science Ltd 2017-03-06 /pmc/articles/PMC5481856/ /pubmed/28670471 http://dx.doi.org/10.4155/fsoa-2017-0001 Text en © Jürgen Bajorath This work is licensed under a Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/)
spellingShingle Perspective
Hu, Ye
Bajorath, Jürgen
Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
title Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
title_full Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
title_fullStr Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
title_full_unstemmed Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
title_short Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
title_sort entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5481856/
https://www.ncbi.nlm.nih.gov/pubmed/28670471
http://dx.doi.org/10.4155/fsoa-2017-0001
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