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Towards reproducible computational drug discovery
Mahidol Univ, Ctr Data Min & Biomed Informat, Fac Med Technol, Bangkok 10700, Thailand.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.ORCID iD: 0000-0001-6740-9212
Kasetsart Univ, Interdisciplinary Grad Program Biosci, Fac Sci, Bangkok 10900, Thailand.
King Mongkuts Inst Technol Ladkrabang, Dept Biomed Engn, Fac Engn, Bangkok 10520, Thailand.
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2020 (English)In: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 12, no 1, article id 9Article, review/survey (Refereed) Published
Abstract [en]

The reproducibility of experiments has been a long standing impediment for further scientific progress. Computational methods have been instrumental in drug discovery efforts owing to its multifaceted utilization for data collection, pre-processing, analysis and inference. This article provides an in-depth coverage on the reproducibility of computational drug discovery. This review explores the following topics: (1) the current state-of-the-art on reproducible research, (2) research documentation (e.g. electronic laboratory notebook, Jupyter notebook, etc.), (3) science of reproducible research (i.e. comparison and contrast with related concepts as replicability, reusability and reliability), (4) model development in computational drug discovery, (5) computational issues on model development and deployment, (6) use case scenarios for streamlining the computational drug discovery protocol. In computational disciplines, it has become common practice to share data and programming codes used for numerical calculations as to not only facilitate reproducibility, but also to foster collaborations (i.e. to drive the project further by introducing new ideas, growing the data, augmenting the code, etc.). It is therefore inevitable that the field of computational drug design would adopt an open approach towards the collection, curation and sharing of data/code.

Place, publisher, year, edition, pages
2020. Vol. 12, no 1, article id 9
Keywords [en]
Reproducibility, Reproducible research, Drug discovery, Drug design, Open science, Open data, Data sharing, Data science, Bioinformatics, Cheminformatics
National Category
Bioinformatics (Computational Biology) Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-407484DOI: 10.1186/s13321-020-0408-xISI: 000513586900002OAI: oai:DiVA.org:uu-407484DiVA, id: diva2:1416828
Note

Nalini Schaduangrat, Samuel Lampa and Saw Simeon contributed equally to this work.

Available from: 2020-03-25 Created: 2020-03-25 Last updated: 2020-03-25Bibliographically approved

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