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Reproducible Research in Computational Science
Open accessAbstract
Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.
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“The difficulty in auditing spreadsheets makes them generally incompatible with the principles of computational reproducibility [5].”
From Gene name errors: Lessons not learned (2021) · cites this paper as [5]
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“The rough consensus reduces to three ingredients.”
From Designing reproducible large-language-model-assisted scientific analyses (2026) · cites this paper as [2]
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“We develop a two-step attribution process which combines a transparent and reproducible 39,40 machine learning approach to identifying studies on observed climate impacts with model-based assessments of detectable anthropogenic contributions to historical temperature and precipitation trends.”
From Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies (2021) · cites this paper as [39]
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Repeatability of published microarray gene expression analyses
Ioannidis, J. P. A., Allison, D. B., Ball, C. A., Coulibaly, I., Cui, X., Culhane, A. C., Falchi, M., Furlanello, C., Game, L., Jurman, G., et al. (2009) · Nature Genetics · doi:10.1038/ng.295 · Cited by 551
King, G. (1995) · PS Political Science & Politics · doi:10.1017/s1049096500057607 · Cited by 473
Publish your computer code: it is good enough
Barnes, N. (2010) · Nature · doi:10.1038/467753a · Cited by 317
Accessible Reproducible Research
Mesirov, J. P. (2010) · Science · doi:10.1126/science.1179653 · Cited by 311
Reproducible Epidemiologic Research
Peng, R. D., Dominici, F., & Zeger, S. L. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj093 · Cited by 292
Self-citationReproducible research and Biostatistics
Peng, R. D. (2009) · Biostatistics · doi:10.1093/biostatistics/kxp014 · Cited by 245
Self-citationMaking scientific computations reproducible
Schwab, M., Karrenbach, N., & Claerbout, J. F. (2000) · Computing in Science & Engineering · doi:10.1109/5992.881708 · Cited by 232
Reproducible Research: Moving toward Research the Public Can Really Trust
Laine, C., Goodman, S. N., Griswold, M. E., & Sox, H. C. (2007) · Annals of Internal Medicine · doi:10.7326/0003-4819-146-6-200703200-00154 · Cited by 213
Making Data Maximally Available
Hanson, B., Sugden, A. M., & Alberts, B. (2011) · Science · doi:10.1126/science.1203354 · Cited by 172
King, G. (1995) · PS Political Science & Politics · doi:10.2307/420301 · Cited by 145
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Schnell, S. D. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004385 · Cited by 67
Austin, C. C., Bloom, T., Dallmeier-Tiessen, S., Khodiyar, V., Murphy, F. L. M., Nurnberger, A., Raymond, L., Stockhause, M., Tedds, J. A., Vardigan, M., et al. (2016) · International Journal on Digital Libraries · doi:10.1007/s00799-016-0178-2 · Cited by 77
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Haakensen, V. D., Nygaard, V., Greger, L., Aure, M. R. R., Fromm, B., Bukholm, I., Lüders, T., Chin, S., Git, A., Caldas, C., et al. (2016) · International Journal of Cancer · doi:10.1002/ijc.30142 · Cited by 65
Ayllón, D., Railsback, S. F., Gallagher, C. A., Augusiak, J., Baveco, J. M., Berger, U., Charles, S., Martin, R., Focks, A., Galić, N., et al. (2020) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2020.104932 · Cited by 65
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Diggle, P. J. (2015) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12132 · Cited by 65
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Shepperd, M., Ajienka, N., & Counsell, S. (2018) · Information and Software Technology · doi:10.1016/j.infsof.2018.01.006 · Cited by 67
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Holmes, M. H. (2016) · Texts in computational science and engineering · doi:10.1007/978-3-319-30256-0_1 · Cited by 65
The de novo genome assembly and annotation of a female domestic dromedary of North African origin
Fitak, R. R., Mohandesan, E., Corander, J., & Burger, P. A. (2015) · Molecular Ecology Resources · doi:10.1111/1755-0998.12443 · Cited by 66
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Borsting, E. A., DeSimone, R., Ascha, M. S., & Ascha, M. (2019) · Journal of Craniofacial Surgery · doi:10.1097/scs.0000000000005905 · Cited by 69
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de Buyl, P., Colberg, P. H., & Höfling, F. (2014) · Computer Physics Communications · doi:10.1016/j.cpc.2014.01.018 · Cited by 64
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Doshi, P., Goodman, S. N., & Ioannidis, J. P. A. (2013) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2013.10.006 · Cited by 63
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Baxter, P. E., Kennedy, J., Senft, E., Lemaignan, S., & Belpaeme, T. (2016) · Lincoln Repository (University of Lincoln) · Cited by 63
VIRULIGN: fast codon-correct alignment and annotation of viral genomes
Libin, P., Deforche, K., Abecasis, A. B., & Theys, K. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty851 · Cited by 63
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Dror, R., Baumer, G., Bogomolov, M., & Reichart, R. (2017) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00074 · Cited by 63
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Dafoe, A. (2013) · PS Political Science & Politics · doi:10.1017/s104909651300173x · Cited by 67
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Gould, R. L. (2021) · Teaching Statistics · doi:10.1111/test.12267 · Cited by 59
Shaqour, A., & Hagishima, A. (2022) · Energies · doi:10.3390/en15228663 · Cited by 59
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Gatto, L., Breckels, L. M., Naake, T., & Gibb, S. (2015) · PROTEOMICS · doi:10.1002/pmic.201400392 · Cited by 59
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Giraud, J., Ogarko, V., Martin, R., Jessell, M., & Lindsay, M. (2021) · Geoscientific model development · doi:10.5194/gmd-14-6681-2021 · Cited by 58
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Janssen, M. A., Pritchard, C., & Lee, A. (2020) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2020.104873 · Cited by 57
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Rollins, N. D., Barton, C. M., Bergin, S. M., Janssen, M. A., & Lee, A. (2014) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2014.06.022 · Cited by 56
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Gant, T. W., Sauer, U. G., Zhang, S., Chorley, B. N., Hackermüller, J., Perdichizzi, S., Tollefsen, K. E., van Ravenzwaay, B., Yauk, C. L., Tong, W., et al. (2017) · Regulatory Toxicology and Pharmacology · doi:10.1016/j.yrtph.2017.11.001 · Cited by 58
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Lewis, K. P., Wal, E. V., & Fifield, D. A. (2018) · Wildlife Society Bulletin · doi:10.1002/wsb.847 · Cited by 54
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Medley, K., Choi, K., König, M., Smith, L. P., Gu, S., Hellerstein, J. L., Sealfon, S. C., & Sauro, H. M. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006220 · Cited by 57
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Maden, S. K., Kwon, S. H., Huuki-Myers, L. A., Collado‐Torres, L., Hicks, S. C., & Maynard, K. R. (2023) · Genome biology · doi:10.1186/s13059-023-03123-4 · Cited by 58
ideal: an R/Bioconductor package for interactive differential expression analysis
Marini, F., Linke, J., & Binder, H. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03819-5 · Cited by 59
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Noacco, V., Sarrazin, F., Pianosi, F., & Wagener, T. (2019) · MethodsX · doi:10.1016/j.mex.2019.09.033 · Cited by 53
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Liu, D. M., & Salganik, M. J. (2019) · Socius Sociological Research for a Dynamic World · doi:10.1177/2378023119849803 · Cited by 47
Aarts, E., Fleuren, H. A., Sitskoorn, M. M., & Wilthagen, T. (2021) · Springer eBooks · doi:10.1007/978-3-030-65355-2 · Cited by 51
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Whelan, G., Kim, K., Pelton, M. A., Soller, J. A., Castleton, K. J., Molina, M., Pachepsky, Y. A., & Zepp, R. G. (2014) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2013.12.013 · Cited by 39
A decade of RAPID—Reflections on the development of an open source geoscience code
David, C. H., Famiglietti, J. S., Yang, Z., Florence Habets, L., & Maidment, D. R. (2016) · Earth and Space Science · doi:10.1002/2015ea000142 · Cited by 39
Metadata
- Authors
- Peng, R. D.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Peng, Roger D.
- ORCID
- Peng, Roger D.
- Venue
- Science
- Published
- 2011-12-02
- Volume
- 334
- Issue
- 6060
- Pages
- 1226-1227
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC3383002
- OpenAlex
- W2008985174
- Semantic Scholar
- e4625641d1072542315c14083befb43cd7096aba
- Cited by
- 1,449
- References
- 11
- Citations by year
- 2026: 162 · 2025: 75 · 2024: 63 · 2023: 74 · 2022: 85 · 2021: 121 · 2020: 139 · 2019: 162 · 2018: 138 · 2017: 113 · 2016: 106 · 2015: 82 · 2014: 51 · 2013: 46 · 2012: 29
- FWCI
- 98.43
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Environmental Health Sciences (R01ES019560)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Social Sciences › Library and Information Sciences › Academic Publishing and Open Access
- Keywords
- reproducible research, scientific computing, reproducibility, scientific claims, replication
- MeSH terms
- Computers, Publishing, Research, Reproducibility of Results, Computational Biology, Editorial Policies, Biomedical Research, Biostatistics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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