Reproducible Research in Computational Science

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

Replication, Replication

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

Reproducible research and Biostatistics

Peng, R. D. (2009) · Biostatistics · doi:10.1093/biostatistics/kxp014 · Cited by 245

Making 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

Replication, Replication

King, G. (1995) · PS Political Science & Politics · doi:10.2307/420301 · Cited by 145

Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research

Zaragozí, B., Trilles, S., & Carrión, J. T. N. (2020) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi9030138 · Cited by 17

Benchmarking in cluster analysis: A white paperPreprint

Mechelen, I. V., Boulesteix, A., Dangl, R., Dean, N., Guyon, I., Hennig, C. M., Leisch, F., & Steinley, D. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.10496 · Cited by 17

The Meaning of Failed Replications: A Review and ProposalPreprint

Clemens, M. A. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2601686 · Cited by 17

On the Reproducibility of Neural Network PredictionsPreprint

Bhojanapalli, S., Wilber, M. J., Veit, A., Rawat, A. S., Kim, S., Menon, A. K., & Kumar, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.03349 · Cited by 17

Reproducible Research in Vadose Zone Sciences

Skaggs, T. H., Young, M. H., & Vrugt, J. A. (2015) · Vadose Zone Journal · doi:10.2136/vzj2015.06.0088 · Cited by 15

An implementation framework to improve the transparency and reproducibility of computational models of infectious diseases

Pokutnaya, D. Y., Childers, B. R., Arcury‐Quandt, A. E., Hochheiser, H., & van Panhuis, W. G. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010856 · Cited by 20

Elevating the RRE Framework for Geospatial Analysis with Visual Programming Platforms: An Exploration with Geospatial Analytics Extension for KNIME

Liu, L., Wang, F., Fu, X., Kötter, T., Sturm, K., Guan, W. W., & Bao, S. (2024) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2024.103948 · Cited by 16

Rigor and reproducibility for data analysis and design in the behavioral sciences

Hildebrandt, T., & Prenoveau, J. M. (2020) · Behaviour Research and Therapy · doi:10.1016/j.brat.2020.103552 · Cited by 17

Automated Water Supply Model (AWSM): Streamlining and standardizing application of a physically based snow model for water resources and reproducible science

Havens, S. C., Marks, D. G., Sandusky, M., Hedrick, A. R., Johnson, M., Robertson, M., & Trujillo, E. (2020) · Computers & Geosciences · doi:10.1016/j.cageo.2020.104571 · Cited by 16

Knowledge and Attitudes Among Life Scientists Toward Reproducibility Within Journal Articles: A Research Survey

Samota, E. K., & Davey, R. (2021) · Frontiers in Research Metrics and Analytics · doi:10.3389/frma.2021.678554 · Cited by 23

A Python-based programming language for high-performance computational genomics

Shajii, A., Numanagić, I., Leighton, A. T., Greenyer, H. W., Amarasinghe, S. P., & Berger, B. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00985-6 · Cited by 16

A new method for testing reproducibility in systematic reviews was developed, but needs more testing

Pieper, D., Heß, S., & Faggion, C. M. (2021) · BMC Medical Research Methodology · doi:10.1186/s12874-021-01342-6 · Cited by 17

Implementing GitHub Actions continuous integration to reduce error rates in ecological data collection

Kim, A. Y., Herrmann, V., Barreto, R., Calkins, B., Gonzalez‐Akre, E. B., Johnson, D. J., Jordan, J. A., Magee, L. J., McGregor, I. R., Montero, N., et al. (2022) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13982 · Cited by 16

An attempt to reproduce a previous meta-analysis and a new analysis regarding the impact of directly observed therapy on tuberculosis treatment outcomes

McKay, B., Castellanos, M. E., Ebell, M. H., Whalen, C. C., & Handel, A. (2019) · PLoS ONE · doi:10.1371/journal.pone.0217219 · Cited by 16

Large language models in peer review: challenges and opportunities

Sun, Z. (2025) · Scientometrics · doi:10.1007/s11192-025-05440-w · Cited by 15

Word final schwa is driven by intonation—The case of Bari Italian

Grice, M., Savino, M., & Roettger, T. B. (2018) · The Journal of the Acoustical Society of America · doi:10.1121/1.5030923 · Cited by 15

Four erroneous beliefs thwarting more trustworthy research

Yarborough, M. A., Nadon, R., & Karlin, D. (2019) · eLife · doi:10.7554/elife.45261 · Cited by 17

The State of Play of Reproducibility in Statistics: An Empirical Analysis

Xiong, X., & Cribben, I. (2022) · The American Statistician · doi:10.1080/00031305.2022.2131625 · Cited by 24

The next generation of fatigue prediction models: evaluating current trends in biomathematical modelling

Wilson, M. K., Strickland, L. J. G., Ballard, T., & Griffin, M. A. (2022) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2022.2144962 · Cited by 15

We don't know what you did last summer. On the importance of transparent reporting of reaction time data pre-processing

Loenneker, H. D., Buchanan, E. M., Martinovici, A., Primbs, M. A., Elsherif, M. M., Baker, B. J., Dudda, L. A., Đurđević, D. F., Mišić, K., Peetz, H. K., et al. (2023) · Cortex · doi:10.1016/j.cortex.2023.11.012 · Cited by 19

Identifying restrictions in the order of accumulation of mutations during tumor progression: effects of passengers, evolutionary models, and sampling

Díaz‐Uriarte, R. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0466-7 · Cited by 15

Recent advances in time-domain seismic imaging

Fomel, S. B. (2014) · Second International Meeting for Applied Geoscience & Energy · doi:10.1190/segam2014-1461.1 · Cited by 15

Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics

Mesnard, O., & Barba, L. A. (2019) · Computing in Science & Engineering · doi:10.1109/mcse.2019.2941702 · Cited by 15

Implementing Computational Reproducibility in the Whole Tale Environment

Chard, K., Gaffney, N. I., Jones, M. B., Kowalik, K., Ludäscher, B., Nabrzyski, J., Stodden, V., Taylor, I., Turk, M., & Willis, C. (2019) · International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS) · doi:10.1145/3322790.3330594 · Cited by 15

Smartphones within Psychological Science

Ellis, D. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108671408 · Cited by 14

Banking with precision: transfusion medicine as a potential universal application in clinical genomics

Montemayor, C., Brunker, P. A. R., & Keller, M. (2019) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000536 · Cited by 17

Reproducibility and replicability of rodent phenotyping in preclinical studiesPreprint

Kafkafi, N., Agassi, J., Chesler, E. J., Crabbe, J. C., Crusio, W. E., Eilam, D., Gerlai, R. T., Golani, I., Gómez-Marín, À., Heller, R., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/079350 · Cited by 16

FAIR and Open Computer Science Research SoftwarePreprint

Hasselbring, W., Carr, L. A., Hettrick, S., Packer, H. S., & Tiropanis, T. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.05986 · Cited by 15

One finding is no finding: Toward a replication culture in family business research

Brinkerink, J., Massis, A. D., & Kellermanns, F. W. (2022) · Journal of Family Business Strategy · doi:10.1016/j.jfbs.2022.100521 · Cited by 17

A rigorous uncertainty-aware quantification framework is essential for reproducible and replicable machine learning workflows

Pouchard, L. C., Reyes, K. G., Alexander, F. J., & Yoon, B.-J. (2023) · Digital Discovery · doi:10.1039/d3dd00094j · Cited by 15

Unraveling trust management in cybersecurity: insights from a systematic literature review

Pigola, A., & Meirelles, F. D. S. (2024) · Information Technology and Management · doi:10.1007/s10799-024-00438-x · Cited by 14

The other N: The role of repetitions and items in the design of phonetic experiments.

Winter, B. (2015) · ICPhS · Cited by 14

Efficacy and safety of B-cell receptor signaling pathway inhibitors in relapsed/refractory chronic lymphocytic leukemia: a systematic review and meta-analysis of randomized clinical trials

Pula, A. E., Stawiski, K., Braun, M., Iskierka‐Jazdzewska, E., & Robak, T. (2017) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2017.1375101 · Cited by 15

All models are wrong, some are useful, but are they reproducible? Commentary on Lee et al. (2019)

Wilson, M. K., Boag, R. J., & Strickland, L. J. G. (2019) · Computational Brain & Behavior · doi:10.1007/s42113-019-00054-x · Cited by 14

Benchmark Dataset for Training Machine Learning Models to Predict the Pathway Involvement of Metabolites

Huckvale, E. D., Powell, C. D., Jin, H., & Moseley, H. (2023) · Metabolites · doi:10.3390/metabo13111120 · Cited by 14

Verification, Validation, and Replication Methods for Agent-Based Modeling and Simulation: Lessons Learned the Hard Way!

Arifin, S. M. N., & Madey, G. R. (2015) · Simulation foundations, methods and applications · doi:10.1007/978-3-319-15096-3_10 · Cited by 14

Markdoc: Literate Programming in Stata

Haghish, E. F. (2016) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x1601600409 · Cited by 14

Using the Raspberry Pi and Docker for Replicable Performance Experiments

Knoche, H., & Eichelberger, H. (2018) · ACM/SPEC International Conference on Performance Engineering (ICPE) · doi:10.1145/3184407.3184431 · Cited by 14

Modeling and Experimental Design for MOOC Dropout Prediction: A Replication Perspective.

Gardner, J., Yang, Y., Baker, R. S., & Brooks, C. A. (2019) · Educational Data Mining · Cited by 14

The Future of Notebook Programming Is Fluid

Kery, M. B., Ren, D., Wongsuphasawat, K., Hohman, F., & Patel, K. (2020) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3334480.3383085 · Cited by 16

Application of Systems Engineering Principles and Techniques in Biological Big Data Analytics: A Review

He, Q., & Wang, J. (2020) · Processes · doi:10.3390/pr8080951 · Cited by 17

An Invitation to Teaching Reproducible Research: Lessons from a Symposium

Ball, R. J., Medeiros, N., Bussberg, N. W., & Piekut, A. (2022) · Journal of Statistics and Data Science Education · doi:10.1080/26939169.2022.2099489 · Cited by 14

T reebase: an R package for discovery, access and manipulation of online phylogenies

Boettiger, C., & Lang, D. T. (2012) · Methods in Ecology and Evolution · doi:10.1111/j.2041-210x.2012.00247.x · Cited by 14

Transparency and Reproducible Research in Modeling

Smith-Spangler, C. M. (2012) · Medical Decision Making · doi:10.1177/0272989x12458977 · Cited by 14

Changing computational research. The challenges ahead

Neylon, C., Aerts, J. A., Brown, C. T., Coles, S. J., Hatton, L., Daniel Lemire, A., Millman, J., Murray‐Rust, P., Pérez, F., Saunders, N. F. W., et al. (2012) · Source Code for Biology and Medicine · doi:10.1186/1751-0473-7-2 · Cited by 14

Code sharing in ecology and evolution increases citation rates but remains uncommon

Maitner, B., Andrade, P. E. S., Lei, L., Kass, J. M., Owens, H. L., Barbosa, G. C. G., Boyle, B. L., Castorena, M., Enquist, B. J., Feng, X., et al. (2024) · Ecology and Evolution · doi:10.1002/ece3.70030 · Cited by 17

Novel machine learning applications in peripartum care: a scoping review

Steinberg, S., Wong, M., Zimlichman, E., & Tsur, A. (2025) · American Journal of Obstetrics & Gynecology MFM · doi:10.1016/j.ajogmf.2025.101612 · Cited by 17

Statistical Perspectives on Reproducibility: Definitions and Challenges

Simkus, A., Coolen‐Maturi, T., Coolen, F. P. A., & Bendtsen, C. (2025) · Journal of Statistical Theory and Practice · doi:10.1007/s42519-025-00459-x · Cited by 14

Replication of Quantitative Work in Development Studies: Experiences and Suggestions

Duvendack, M., & Palmer‐Jones, R. (2014) · Palgrave Macmillan UK eBooks · doi:10.1057/9781137293626_11 · Cited by 13

Gender Interacts with Opioid Receptor Polymorphism A118G and Serotonin Receptor Polymorphism −1438 A/G on Speed-Dating Success

Wu, K. L., Chen, C., Moyzis, R. K., Greenberger, E., & Yu, Z. (2016) · Human Nature · doi:10.1007/s12110-016-9257-8 · Cited by 14

Continuous Reproducibility in GNSS Signal Processing

Fernández–Prades, C., Vilà‐Valls, J., Arribas, J., & Ramos, A. (2018) · IEEE Access · doi:10.1109/access.2018.2822835 · Cited by 12

The current phase of social sciences research: A thematic overview of the literature

Babalola, S. S., & Nwanzu, C. L. (2021) · Cogent Social Sciences · doi:10.1080/23311886.2021.1892263 · Cited by 16

Design Principles for Data Analysis

McGowan, L. D., Peng, R. D., & Hicks, S. C. (2022) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2022.2104290 · Cited by 13

A framework for ecosystem service assessment using GIS interoperability standards

Lacayo, M., Rodila, D. D., Giuliani, G., & Lehmann, A. (2021) · Computers & Geosciences · doi:10.1016/j.cageo.2021.104821 · Cited by 13

A note on rigour and replicability

Λουρίδας, Π., & Gousios, G. (2012) · ACM SIGSOFT Software Engineering Notes · doi:10.1145/2347696.2347706 · Cited by 13

Data science for the scientific life cycle

Ezer, D., & Whitaker, K. (2019) · eLife · doi:10.7554/elife.43979 · Cited by 14

Making simulation results reproducible—Survey, guidelines, and examples based on Gradle and Docker

Elmenreich, W., Moll, P., Theuermann, S., & Lux, M. (2019) · PeerJ Computer Science · doi:10.7717/peerj-cs.240 · Cited by 13

samExploreR: exploring reproducibility and robustness of RNA-seq results based on SAM files

Stupnikov, A., Tripathi, S., Simoes, R. D. M., McArt, D. G., Salto‐Tellez, M., Glazko, G. V., Dehmer, M., & Emmert‐Streib, F. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw475 · Cited by 13

FullSWOF: A free software package for the simulation of shallow water flowsPreprint

Delestre, O., Darboux, F., James, F., Lucas, C., Laguerre, C., & Cordier, S. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1401.4125 · Cited by 13

Performance Benchmarking of Application Monitoring Frameworks

Waller, J. (2014) · Multimedialen Archiv und Publikationsserver der Christian-Albrechts-Universität zu Kiel (Christian-Albrechts-Universität zu Kiel) · Cited by 13

Computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes

Peters, K., Gorzolka, K., Bruelheide, H., & Neumann, S. (2018) · Scientific Data · doi:10.1038/sdata.2018.179 · Cited by 12

Reproducibility improves exponentially over 63 years of social learning researchPreprint

Minocher, R., Atmaca, S., Bavero, C., McElreath, R. L., & Beheim, B. (2020) · doi:10.31234/osf.io/4nzc7 · Cited by 13

Stabilizing machine learning for reproducible and explainable results: A novel validation approach to subject-specific insights

Vos, G., van Eijk, L., Sarnyai, Z., & Azghadi, M. R. (2025) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2025.108899 · Cited by 15

Grand Challenges for Artificial Intelligence in Molecular Medicine

Emmert‐Streib, F. (2021) · Frontiers in Molecular Medicine · doi:10.3389/fmmed.2021.734659 · Cited by 14

Raising the Bar for Reproducible Science at the U.S. Environmental Protection Agency Office of Research and Development

George, B. J., Sobus, J. R., Phelps, L. P., Rashleigh, B., Simmons, J. E., Hines, R. N., & Groups, T. C. O. P. F. S. G. D. W. (2015) · Toxicological Sciences · doi:10.1093/toxsci/kfv020 · Cited by 14

A very simple and fast way to access and validate algorithms in reproducible research

Stegmayer, G. S., Pividori, M., & Milone, D. H. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv054 · Cited by 12

BINSYN: A Publicly Available Program for Simulating Spectra and Light Curves of Binary Systems with or without Accretion Disks

Linnell, A. P., DeStefano, P. R., & Hubený, I. (2012) · Publications of the Astronomical Society of the Pacific · doi:10.1086/667217 · Cited by 12

Standards for Documenting Finite‐Fault Earthquake Rupture Models

Martín, P., Shearer, P. M., Ampuero, J., & Lay, T. (2016) · Seismological Research Letters · doi:10.1785/0220150204 · Cited by 12

Evaluation of the OntoSoft Ontology for describing metadata for legacy hydrologic modeling software

Essawy, B. T., Goodall, J. L., Xu, H., & Gil, Y. (2017) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2017.01.024 · Cited by 12

hydroscoper: R interface to the Greek National Data Bank for Hydrological and Meteorological Information

Vantas, K. (2018) · The Journal of Open Source Software · doi:10.21105/joss.00625 · Cited by 12

Visually guided preprocessing of bioanalytical laboratory data using an interactive R notebook (pguIMP)

Malkusch, S., Hahnefeld, L., Gurke, R., & Lötsch, J. (2021) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12704 · Cited by 12

A long-term monitoring database on fish and crayfish species in French rivers

Irz, P., Vigneron, T., Poulet, N., Cosson, E., POINT, T., BAGLINIERE, E., & Porcher, J. (2022) · Knowledge and Management of Aquatic Ecosystems · doi:10.1051/kmae/2022021 · Cited by 12

Reproducibility in Machine Learning for Medical Imaging

Olivier Colliot, A., Thibeau–Sutre, E., & Burgos, N. (2023) · Neuromethods · doi:10.1007/978-1-0716-3195-9_21 · Cited by 16

In‐depth analysis of patterns in selection of different physiologically based pharmacokinetic modeling tools: Part I – Applications and rationale behind the use of open source‐code software

Rajput, A. J., Aldibani, H. K. A., & Rostami‐Hodjegan, A. (2023) · Biopharmaceutics & Drug Disposition · doi:10.1002/bdd.2357 · Cited by 12

Using object-based image analysis to determine seafloor fine-scale features and complexity

Lacharité, M., Meta×as, A., & Lawton, P. (2015) · Limnology and Oceanography Methods · doi:10.1002/lom3.10047 · Cited by 12

Development of a cloud-based platform for reproducible science: A case study of an IUCN Red List of Ecosystems Assessment

Guru, S. M., Hanigan, I., Nguyen, H. A., Burns, E., Stein, J., Blanchard, W., Lindenmayer, D. B., & Clancy, T. (2016) · Ecological Informatics · doi:10.1016/j.ecoinf.2016.08.003 · Cited by 10

PyMICE: APython library for analysis of IntelliCage data

Dzik, J. M., Puścian, A., Harda, Z., Radwańska, K., & Łęski, S. (2017) · Behavior Research Methods · doi:10.3758/s13428-017-0907-5 · Cited by 11

Visualising three-dimensional genome organisation in two dimensions

Ing‐Simmons, E., & Vaquerizas, J. M. (2019) · Development · doi:10.1242/dev.177162 · Cited by 13

Truth, Proof, and Reproducibility: There’s No Counter-Attack for the Codeless

Gray, C. T., & Marwick, B. (2019) · Communications in computer and information science · doi:10.1007/978-981-15-1960-4_8 · Cited by 11

Beyond Standardization: Improving External Validity and Reproducibility in Experimental Evolution

Desjardins, E., Kurtz, J., Kranke, N., Lindeza, A. S., & Richter, S. H. (2021) · BioScience · doi:10.1093/biosci/biab008 · Cited by 12

Procedural Generation of 3D Maps With Snappable Meshes

Silva, R. C. E., Fachada, N., de Andrade, D., & Códices, N. (2022) · IEEE Access · doi:10.1109/access.2022.3168832 · Cited by 11

Reproducible Research for Computing in Science & Engineering

Barba, L. A., & Thiruvathukal, G. K. (2017) · Computing in Science & Engineering · doi:10.1109/mcse.2017.3971172 · Cited by 12

Toward Open Science at the European Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling

de Rigo, D., Corti, P., Caudullo, G., McInerney, D. O., Leo, M. D., & San-Miguel-Ayanz, J. (2013) · Figshare · doi:10.6084/m9.figshare.155703 · Cited by 12

MultiCellDS: a community-developed standard for curating microenvironment-dependent multicellular dataPreprint

Friedman, S. H., Anderson, A. R. A., Bortz, D. M., Fletcher, A. G., Frieboes, H. B., Ghaffarizadeh, A., Grimes, D. R., Hawkins-Daarud, A. J., Hoehme, S., Juarez, E. F., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/090456 · Cited by 12

Ten simple rules for building and maintaining a responsible data science workflow

Stoudt, S., Jernite, Y., Marshall, B., Marwick, B., Sharan, M., Whitaker, K., & Danchev, V. (2024) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1012232 · Cited by 11

Reproducible Tract Profiles 2 (RTP2) suite, from diffusion MRI acquisition to clinical practice and research

Lerma‐Usabiaga, G., Liu, M., Paz‐Alonso, P. M., & Wandell, B. A. (2023) · Scientific Reports · doi:10.1038/s41598-023-32924-7 · Cited by 11

On Process Discovery Experimentation: Addressing the Need for Research Methodology in Process Discovery

Rehse, J.-R., Leemans, S. J. J., Fettke, P., & van der Werf, J. M. E. M. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3672447 · Cited by 11

How can we make sound replication decisions?

Davis‐Stober, C. P., Sarafoglou, A., Aczél, B., Chandramouli, S., Errington, T. M., Field, S. M., Fishbach, A., Freire, J., Ioannidis, J. P. A., Oberauer, K., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2401236121 · Cited by 13

Reproducible Research in Document Analysis and Recognition

Cacho, J. R. F., & Taghva, K. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-77028-4_51 · Cited by 11

NuRsing Research in the 21st Century: R You Ready?

Wright, M. L., Higgins, M. K., Taylor, J. Y., & Hertzberg, V. (2018) · Biological Research For Nursing · doi:10.1177/1099800418810514 · Cited by 11

Software and Dependencies in Research Citation Graphs

Druskat, S. (2019) · Computing in Science & Engineering · doi:10.1109/mcse.2019.2952840 · Cited by 11

Perspective on Data Science

Peng, R. D., & Parker, H. S. (2021) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-040220-013917 · Cited by 12

A cautionary tale about properly vetting datasets used in supervised learning predicting metabolic pathway involvement

Huckvale, E. D., & Moseley, H. (2024) · PLoS ONE · doi:10.1371/journal.pone.0299583 · Cited by 11

sgnesR: An R package for simulating gene expression data from an underlying real gene network structure considering delay parameters

Tripathi, S., Lloyd‐Price, J., Ribeiro, A. S., Yli-Harja, O. P., Dehmer, M., & Emmert‐Streib, F. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1731-8 · Cited by 11

IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms

Ishikawa, N. (2019) · IEEE Access · doi:10.1109/access.2019.2928033 · Cited by 11

State of the Art in Paleoenvironment Mapping for Modeling Applications in Archeology—Summary, Conclusions, and Future Directions from the PaleoMaps Workshop

Willmes, C., Niedziółka, K., Serbe, B., Grimm, S., Groß, D., Miebach, A., Maerker, M., Henselowsky, F., Gamisch, A., Rostami, M., et al. (2020) · Quaternary · doi:10.3390/quat3020013 · Cited by 11

Review of the application of the open-source software CilOCT for semi-automatic segmentation and analysis of the ciliary muscle in OCT images

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