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Systematic benchmarking of omics computational tools

Computational omics methods packaged as software have become essential to modern biological research. The increasing dependence of scientists on these powerful software tools creates a need for systematic assessment of these methods, known as benchmarking. Adopting a standardized benchmarking practi...

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Detalles Bibliográficos
Autores principales: Mangul, Serghei, Martin, Lana S., Hill, Brian L., Lam, Angela Ka-Mei, Distler, Margaret G., Zelikovsky, Alex, Eskin, Eleazar, Flint, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437167/
https://www.ncbi.nlm.nih.gov/pubmed/30918265
http://dx.doi.org/10.1038/s41467-019-09406-4
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author Mangul, Serghei
Martin, Lana S.
Hill, Brian L.
Lam, Angela Ka-Mei
Distler, Margaret G.
Zelikovsky, Alex
Eskin, Eleazar
Flint, Jonathan
author_facet Mangul, Serghei
Martin, Lana S.
Hill, Brian L.
Lam, Angela Ka-Mei
Distler, Margaret G.
Zelikovsky, Alex
Eskin, Eleazar
Flint, Jonathan
author_sort Mangul, Serghei
collection PubMed
description Computational omics methods packaged as software have become essential to modern biological research. The increasing dependence of scientists on these powerful software tools creates a need for systematic assessment of these methods, known as benchmarking. Adopting a standardized benchmarking practice could help researchers who use omics data to better leverage recent technological innovations. Our review summarizes benchmarking practices from 25 recent studies and discusses the challenges, advantages, and limitations of benchmarking across various domains of biology. We also propose principles that can make computational biology benchmarking studies more sustainable and reproducible, ultimately increasing the transparency of biomedical data and results.
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spelling pubmed-64371672019-03-29 Systematic benchmarking of omics computational tools Mangul, Serghei Martin, Lana S. Hill, Brian L. Lam, Angela Ka-Mei Distler, Margaret G. Zelikovsky, Alex Eskin, Eleazar Flint, Jonathan Nat Commun Review Article Computational omics methods packaged as software have become essential to modern biological research. The increasing dependence of scientists on these powerful software tools creates a need for systematic assessment of these methods, known as benchmarking. Adopting a standardized benchmarking practice could help researchers who use omics data to better leverage recent technological innovations. Our review summarizes benchmarking practices from 25 recent studies and discusses the challenges, advantages, and limitations of benchmarking across various domains of biology. We also propose principles that can make computational biology benchmarking studies more sustainable and reproducible, ultimately increasing the transparency of biomedical data and results. Nature Publishing Group UK 2019-03-27 /pmc/articles/PMC6437167/ /pubmed/30918265 http://dx.doi.org/10.1038/s41467-019-09406-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Review Article
Mangul, Serghei
Martin, Lana S.
Hill, Brian L.
Lam, Angela Ka-Mei
Distler, Margaret G.
Zelikovsky, Alex
Eskin, Eleazar
Flint, Jonathan
Systematic benchmarking of omics computational tools
title Systematic benchmarking of omics computational tools
title_full Systematic benchmarking of omics computational tools
title_fullStr Systematic benchmarking of omics computational tools
title_full_unstemmed Systematic benchmarking of omics computational tools
title_short Systematic benchmarking of omics computational tools
title_sort systematic benchmarking of omics computational tools
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437167/
https://www.ncbi.nlm.nih.gov/pubmed/30918265
http://dx.doi.org/10.1038/s41467-019-09406-4
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