Literature DB >> 24361338

Data-driven medicinal chemistry in the era of big data.

Scott J Lusher1, Ross McGuire2, René C van Schaik3, C David Nicholson4, Jacob de Vlieg5.   

Abstract

Science, and the way we undertake research, is changing. The increasing rate of data generation across all scientific disciplines is providing incredible opportunities for data-driven research, with the potential to transform our current practices. The exploitation of so-called 'big data' will enable us to undertake research projects never previously possible but should also stimulate a re-evaluation of all our data practices. Data-driven medicinal chemistry approaches have the potential to improve decision making in drug discovery projects, providing that all researchers embrace the role of 'data scientist' and uncover the meaningful relationships and patterns in available data.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2013        PMID: 24361338     DOI: 10.1016/j.drudis.2013.12.004

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


  17 in total

Review 1.  Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling.

Authors:  Linlin Zhao; Heather L Ciallella; Lauren M Aleksunes; Hao Zhu
Journal:  Drug Discov Today       Date:  2020-07-11       Impact factor: 7.851

Review 2.  Big data in medicine is driving big changes.

Authors:  F Martin-Sanchez; K Verspoor
Journal:  Yearb Med Inform       Date:  2014-08-15

3.  Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge.

Authors:  Jody C May; John A McLean
Journal:  Annu Rev Anal Chem (Palo Alto Calif)       Date:  2016-03-30       Impact factor: 10.745

Review 4.  Rethinking drug design in the artificial intelligence era.

Authors:  Petra Schneider; W Patrick Walters; Alleyn T Plowright; Norman Sieroka; Jennifer Listgarten; Robert A Goodnow; Jasmin Fisher; Johanna M Jansen; José S Duca; Thomas S Rush; Matthias Zentgraf; John Edward Hill; Elizabeth Krutoholow; Matthias Kohler; Jeff Blaney; Kimito Funatsu; Chris Luebkemann; Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2019-12-04       Impact factor: 84.694

5.  Entering new publication territory in chemoinformatics and chemical information science.

Authors:  Jürgen Bajorath
Journal:  F1000Res       Date:  2015-02-04

Review 6.  The antitumor effects of geraniol: Modulation of cancer hallmark pathways (Review).

Authors:  Minsoo Cho; Insuk So; Jung Nyeo Chun; Ju-Hong Jeon
Journal:  Int J Oncol       Date:  2016-03-09       Impact factor: 5.650

7.  Determining the Degree of Promiscuity of Extensively Assayed Compounds.

Authors:  Swarit Jasial; Ye Hu; Jürgen Bajorath
Journal:  PLoS One       Date:  2016-04-15       Impact factor: 3.240

8.  Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis.

Authors:  Divneet Kaur; Shalu Mathew; Chinchu G S Nair; Azitha Begum; Ashwin K Jainanarayan; Mukta Sharma; Samir K Brahmachari
Journal:  J Transl Med       Date:  2017-12-21       Impact factor: 5.531

9.  Computational prediction of microRNA networks incorporating environmental toxicity and disease etiology.

Authors:  Jie Li; Zengrui Wu; Feixiong Cheng; Weihua Li; Guixia Liu; Yun Tang
Journal:  Sci Rep       Date:  2014-07-04       Impact factor: 4.379

Review 10.  Computer-aided drug discovery.

Authors:  Jürgen Bajorath
Journal:  F1000Res       Date:  2015-08-26
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