Literature DB >> 18428092

Scientific workflows as productivity tools for drug discovery.

John Shon1, Hitomi Ohkawa, Juergen Hammer.   

Abstract

Large pharmaceutical companies annually invest tens to hundreds of millions of US dollars in research informatics to support their early drug discovery processes. Traditionally, most of these investments are designed to increase the efficiency of drug discovery. The introduction of do-it-yourself scientific workflow platforms has enabled research informatics organizations to shift their efforts toward scientific innovation, ultimately resulting in a possible increase in return on their investments. Unlike the handling of most scientific data and application integration approaches, researchers apply scientific workflows to in silico experimentation and exploration, leading to scientific discoveries that lie beyond automation and integration. This review highlights some key requirements for scientific workflow environments in the pharmaceutical industry that are necessary for increasing research productivity. Examples of the application of scientific workflows in research and a summary of recent platform advances are also provided.

Mesh:

Year:  2008        PMID: 18428092

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  9 in total

Review 1.  Genetic design automation: engineering fantasy or scientific renewal?

Authors:  Matthew W Lux; Brian W Bramlett; David A Ball; Jean Peccoud
Journal:  Trends Biotechnol       Date:  2011-10-14       Impact factor: 19.536

2.  CDK-Taverna: an open workflow environment for cheminformatics.

Authors:  Thomas Kuhn; Egon L Willighagen; Achim Zielesny; Christoph Steinbeck
Journal:  BMC Bioinformatics       Date:  2010-03-29       Impact factor: 3.169

3.  Scientific workflow systems: Pipeline Pilot and KNIME.

Authors:  Wendy A Warr
Journal:  J Comput Aided Mol Des       Date:  2012-05-27       Impact factor: 3.686

4.  Using workflows to explore and optimise named entity recognition for chemistry.

Authors:  Balakrishna Kolluru; Lezan Hawizy; Peter Murray-Rust; Junichi Tsujii; Sophia Ananiadou
Journal:  PLoS One       Date:  2011-05-25       Impact factor: 3.240

5.  New developments on the cheminformatics open workflow environment CDK-Taverna.

Authors:  Andreas Truszkowski; Kalai Vanii Jayaseelan; Stefan Neumann; Egon L Willighagen; Achim Zielesny; Christoph Steinbeck
Journal:  J Cheminform       Date:  2011-12-13       Impact factor: 5.514

Review 6.  Improving data workflow systems with cloud services and use of open data for bioinformatics research.

Authors:  Md Rezaul Karim; Audrey Michel; Achille Zappa; Pavel Baranov; Ratnesh Sahay; Dietrich Rebholz-Schuhmann
Journal:  Brief Bioinform       Date:  2018-09-28       Impact factor: 11.622

7.  Processing binding data using an open-source workflow.

Authors:  Errol L G Samuel; Secondra L Holmes; Damian W Young
Journal:  J Cheminform       Date:  2021-12-11       Impact factor: 5.514

8.  Translational web robots for pathogen genome analysis.

Authors:  Vitali Sintchenko; Enrico W Coiera
Journal:  Microb Inform Exp       Date:  2011-10-31

Review 9.  Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery.

Authors:  Douglas B Kell; Royston Goodacre
Journal:  Drug Discov Today       Date:  2013-07-26       Impact factor: 7.851

  9 in total

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