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Centralized scientific communities are less likely to generate replicable results
Concerns have been expressed about the robustness of experimental findings in several areas of science, but these matters have not been evaluated at scale. Here we identify a large sample of published drug-gene interaction claims curated in the Comparative Toxicogenomics Database (for example, benzo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606034/ https://www.ncbi.nlm.nih.gov/pubmed/31264964 http://dx.doi.org/10.7554/eLife.43094 |
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author | Danchev, Valentin Rzhetsky, Andrey Evans, James A |
author_facet | Danchev, Valentin Rzhetsky, Andrey Evans, James A |
author_sort | Danchev, Valentin |
collection | PubMed |
description | Concerns have been expressed about the robustness of experimental findings in several areas of science, but these matters have not been evaluated at scale. Here we identify a large sample of published drug-gene interaction claims curated in the Comparative Toxicogenomics Database (for example, benzo(a)pyrene decreases expression of SLC22A3) and evaluate these claims by connecting them with high-throughput experiments from the LINCS L1000 program. Our sample included 60,159 supporting findings and 4253 opposing findings about 51,292 drug-gene interaction claims in 3363 scientific articles. We show that claims reported in a single paper replicate 19.0% (95% confidence interval [CI], 16.9–21.2%) more frequently than expected, while claims reported in multiple papers replicate 45.5% (95% CI, 21.8–74.2%) more frequently than expected. We also analyze the subsample of interactions with two or more published findings (2493 claims; 6272 supporting findings; 339 opposing findings; 1282 research articles), and show that centralized scientific communities, which use similar methods and involve shared authors who contribute to many articles, propagate less replicable claims than decentralized communities, which use more diverse methods and contain more independent teams. Our findings suggest how policies that foster decentralized collaboration will increase the robustness of scientific findings in biomedical research. |
format | Online Article Text |
id | pubmed-6606034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-66060342019-07-03 Centralized scientific communities are less likely to generate replicable results Danchev, Valentin Rzhetsky, Andrey Evans, James A eLife Computational and Systems Biology Concerns have been expressed about the robustness of experimental findings in several areas of science, but these matters have not been evaluated at scale. Here we identify a large sample of published drug-gene interaction claims curated in the Comparative Toxicogenomics Database (for example, benzo(a)pyrene decreases expression of SLC22A3) and evaluate these claims by connecting them with high-throughput experiments from the LINCS L1000 program. Our sample included 60,159 supporting findings and 4253 opposing findings about 51,292 drug-gene interaction claims in 3363 scientific articles. We show that claims reported in a single paper replicate 19.0% (95% confidence interval [CI], 16.9–21.2%) more frequently than expected, while claims reported in multiple papers replicate 45.5% (95% CI, 21.8–74.2%) more frequently than expected. We also analyze the subsample of interactions with two or more published findings (2493 claims; 6272 supporting findings; 339 opposing findings; 1282 research articles), and show that centralized scientific communities, which use similar methods and involve shared authors who contribute to many articles, propagate less replicable claims than decentralized communities, which use more diverse methods and contain more independent teams. Our findings suggest how policies that foster decentralized collaboration will increase the robustness of scientific findings in biomedical research. eLife Sciences Publications, Ltd 2019-07-02 /pmc/articles/PMC6606034/ /pubmed/31264964 http://dx.doi.org/10.7554/eLife.43094 Text en © 2019, Danchev et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Danchev, Valentin Rzhetsky, Andrey Evans, James A Centralized scientific communities are less likely to generate replicable results |
title | Centralized scientific communities are less likely to generate replicable results |
title_full | Centralized scientific communities are less likely to generate replicable results |
title_fullStr | Centralized scientific communities are less likely to generate replicable results |
title_full_unstemmed | Centralized scientific communities are less likely to generate replicable results |
title_short | Centralized scientific communities are less likely to generate replicable results |
title_sort | centralized scientific communities are less likely to generate replicable results |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606034/ https://www.ncbi.nlm.nih.gov/pubmed/31264964 http://dx.doi.org/10.7554/eLife.43094 |
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