Literature DB >> 23758509

Modeling, informatics, and the quest for reproducibility.

W Patrick Walters.   

Abstract

There is no doubt that papers published in the Journal of Chemical Information and Modeling, and related journals, provide valuable scientific information. However, it is often difficult to reproduce the work described in molecular modeling and cheminformatics papers. In many cases the software described in the paper is not readily available, in other cases the supporting information is not provided in an accessible format. To date, the major journals in the fields of molecular modeling and cheminformatics have not established guidelines for reproducible research. This letter provides an overview of the reproducibility challenges facing our field and suggests some guidelines for improving the reproducibility of published work.

Mesh:

Year:  2013        PMID: 23758509     DOI: 10.1021/ci400197w

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  6 in total

1.  Uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike molecules.

Authors:  James L McDonagh; Neetika Nath; Luna De Ferrari; Tanja van Mourik; John B O Mitchell
Journal:  J Chem Inf Model       Date:  2014-03-11       Impact factor: 4.956

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

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

3.  On the evolving open peer review culture for chemical information science.

Authors:  W Patrick Walters; Jürgen Bajorath
Journal:  F1000Res       Date:  2015-11-25

4.  Ten simple rules on how to create open access and reproducible molecular simulations of biological systems.

Authors:  Arne Elofsson; Berk Hess; Erik Lindahl; Alexey Onufriev; David van der Spoel; Anders Wallqvist
Journal:  PLoS Comput Biol       Date:  2019-01-17       Impact factor: 4.475

5.  Making simulation results reproducible-Survey, guidelines, and examples based on Gradle and Docker.

Authors:  Wilfried Elmenreich; Philipp Moll; Sebastian Theuermann; Mathias Lux
Journal:  PeerJ Comput Sci       Date:  2019-12-09

6.  Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Authors:  Matthew C Robinson; Robert C Glen; Alpha A Lee
Journal:  J Comput Aided Mol Des       Date:  2020-01-20       Impact factor: 3.686

  6 in total

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