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 472

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

Inishell 2.0: semantically driven automatic GUI generation for scientific models

Bavay, M., Reisecker, M., Egger, T., & Korhammer, D. (2022) · Geoscientific model development · doi:10.5194/gmd-15-365-2022 · Cited by 7

Rejoinder: An estimate of the science-wise false discovery rate and application to the top medical literature

Jager, L. R., & Leek, J. T. (2013) · Biostatistics · doi:10.1093/biostatistics/kxt038 · Cited by 7

Statistical Modeling of Financial Data with Skew-Symmetric Error Distributions

Jimichi, M., Kawasaki, Y., Miyamoto, D., Saka, C., & Nagata, S. (2023) · Symmetry · doi:10.3390/sym15091772 · Cited by 7

Reproducible Tract Profiles (RTP): from diffusion MRI acquisition to publicationPreprint

Lerma‐Usabiaga, G., Perry, L. M., & Wandell, B. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/680173 · Cited by 7

Guerrilla Badges for Reproducible Geospatial Data Science (AGILE 2019 Short Paper)Preprint

Nüst, D., Lohoff, L., Einfeldt, L., Gavish, N., Götza, M., Jaswal, S., Khalid, S., Meierkort, L., Mohr, M., & Rendel, C. (2019) · doi:10.31223/osf.io/xtsqh · Cited by 9

Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimagingPreprint

Renton, A., Dao, T. T., Abbott, D. F., Amos, T. J., Bollmann, S., Botting, A., Campbell, M. E. J., Chang, J., Civier, O., Close, T., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.23.521691 · Cited by 7

Scientific literature on carbon dioxide removal much larger than previously suggested: insights from an AI-enhanced systematic mapPreprint

Lück, S., Callaghan, M., Borchers, M., Cowie, A., Fuss, S., Geden, O., Gidden, M., Hartmann, J., Kammann, C. I., Keller, D. P., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4109712/v1 · Cited by 7

Kollaps: Decentralized and Efficient Network Emulation for Large-Scale Systems

Amaro, S., Matos, M., & Schiavoni, V. (2024) · IEEE Transactions on Networking · doi:10.1109/tnet.2024.3478050 · Cited by 6

The imperative for reproducibility in building performance simulation research

Ghiaus, C. (2025) · Journal of Building Performance Simulation · doi:10.1080/19401493.2024.2441385 · Cited by 6

Minimal sufficient information about the scientific workflows to create reproducible experiment

Bánáti, A., Kacsuk, P., & Kozlovszky, M. (2015) · IEEE International Conference on Intelligent Engineering Systems (INES) · doi:10.1109/ines.2015.7329705 · Cited by 6

Computational science: shifting the focus from tools to models

Hinsen, K. (2014) · F1000Research · doi:10.12688/f1000research.4263 · Cited by 6

K-span: Open and reproducible spatial analytics using scientific workflows

Forkan, A. R. M., Both, A., Bellman, C. J., Duckham, M., Anderson, H., & Radosevic, N. (2023) · Frontiers in Earth Science · doi:10.3389/feart.2023.1130262 · Cited by 6

On the comparability between studies in predictive ecotoxicology

Schür, C., Schirmer, K., & Baity‐Jesi, M. (2025) · Computational Toxicology · doi:10.1016/j.comtox.2025.100367 · Cited by 7

Towards Reusability of Computational Experiments - Capturing and Sharing Research Objects from Knowledge Discovery Processes

Lefebvre, A., Spruit, M. R., & Omta, W. A. (2015) · International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management · doi:10.5220/0005631604560462 · Cited by 6

Emerging Technologies for Data Research: Implications for Bias, Curation, and Reproducible Results

Worden, D. J. (2017) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-78714-827-720171003 · Cited by 6

Comparing two methods of remotely estimating moulin discharge on the Greenland ice sheet

King, L. (2018) · Journal of Glaciology · doi:10.1017/jog.2018.65 · Cited by 6

Assessing Dimensionality in Non-Positive Definite Tetrachoric Correlation Matrices: Does Matrix Smoothing Help?

Kracht, J. D., & Waller, N. G. (2020) · Multivariate Behavioral Research · doi:10.1080/00273171.2020.1859350 · Cited by 6

Re-discovering Archaeological Discoveries. Experiments with reproducing archaeological survey analysis

Strupler, N. (2021) · Internet Archaeology · doi:10.11141/ia.56.6 · Cited by 6

Computational Reproducibility: A Practical Framework for Data Curators

Sawchuk, S., & Khair, S. (2021) · Journal of eScience Librarianship · doi:10.7191/jeslib.2021.1206 · Cited by 6

A mentorship and incubation program using project-based learning to build a professional bioinformatics pipeline in Kenya

Nanjala, R., Nyasimi, F. M., Masiga, D. K., & Kibet, C. K. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010904 · Cited by 6

On the performance comparison of diagnostic techniques in machine monitoring

Pancaldi, F., Rubini, R., & Cocconcelli, M. (2023) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2023.110872 · Cited by 6

An Outlook for AI Innovation in Multimodal Communication Research

Henlein, A., Bauer, A., Bhattacharjee, R., Ćwiek, A., Gregori, A., Kügler, F., Lemanski, J., Lücking, A., Mehler, A., Prieto, P., et al. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-61066-0_13 · Cited by 6

Recommendations for a standardized publication protocol for a QSP model

Weddell, J. C., Gulati, A., & Yamada, A. (2024) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-024-09943-6 · Cited by 6

CONNJUR R: an annotation strategy for fostering reproducibility in bio-NMR—protein spectral assignment

Fenwick, M., Hoch, J. C., Ulrich, E. L., & Gryk, M. R. (2015) · Journal of Biomolecular NMR · doi:10.1007/s10858-015-9964-1 · Cited by 7

GuideAutomator: Continuous Delivery of End User Documentation

de Souza, R. F., & Oliveira, A. D. S. (2017) · IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER) · doi:10.1109/icse-nier.2017.10 · Cited by 6

AMModels: An R package for storing models, data, and metadata to facilitate adaptive management

Donovan, T. M., & Katz, J. E. (2018) · PLoS ONE · doi:10.1371/journal.pone.0188966 · Cited by 6

Embedding Meta Information into Visualizations

Hota, A., & Huang, J. P. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2019.2916098 · Cited by 6

Agent-Based Modeling, Scientific Reproducibility, and Taphonomy: A Successful Model Implementation Case Study

Carney, M., & Davies, B. (2020) · Journal of Computer Applications in Archaeology · doi:10.5334/jcaa.52 · Cited by 6

Evidence-Based Research in Nursing Science: A Reproducible Framework

Choi, S. (2020) · Western Journal of Nursing Research · doi:10.1177/0193945920977792 · Cited by 6

Experimental Standards for Deep Learning in Natural Language Processing Research

Ulmer, D., Bassignana, E., Müller-Eberstein, M., Varab, D., Zhang, M., van der Goot, R., Hardmeier, C., & Plank, B. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.196 · Cited by 9

Stepping Stones to Reproducible Research: A Study of Current Practices in Parallel Computing

Carpen-Amarie, A., Rougier, A., & Lübbe, F. D. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-14325-5_43 · Cited by 6

MAGPIE: Simplifying access and execution of computational models in the life sciences

Baldow, C., Salentin, S., Schroeder, M., Roeder, I., & Glauche, I. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005898 · Cited by 6

Examining the Reproducibility of 6 Published Studies in Public Health Services and Systems Research

Harris, J. K., Wondmeneh, S. B., Zhao, Y., & Leider, J. P. (2018) · Journal of Public Health Management and Practice · doi:10.1097/phh.0000000000000694 · Cited by 6

Towards Replication in Computational Cognitive Modeling: a Machine Learning Perspective

Emmery, C., Kádár, Á., Wiltshire, T. J., & Hendrickson, A. T. (2019) · Computational Brain & Behavior · doi:10.1007/s42113-019-00055-w · Cited by 6

The Indonesian National Scientific Repository: A Case Study of Research Data Sharing

Anggawira, D., & Mayesti, N. (2020) · Preservation Digital Technology & Culture · doi:10.1515/pdtc-2019-0015 · Cited by 6

Ensembler: A Simple Package for Fast Prototyping and Teaching Molecular Simulations

Ries, B., Linker, S. M., Hahn, D. F., König, G., & Riniker, S. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c01283 · Cited by 6

Free and Open Source Software underpinning the European Forest Data Centre

Dario Rodriguez-aseretto, A., Leo, M. D., de Rigo, D., Corti, P., McInerney, D. O., Camia, A., & San-Miguel-Ayanz, J. (2013) · Figshare · doi:10.6084/m9.figshare.155700 · Cited by 6

Guidelines for reliable and reproducible functional enrichment analysisPreprint

Wijesooriya, K., Jadaan, S. A., Perera, K. L., Kaur, T., & Ziemann, M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.06.459114 · Cited by 6

Reproducible Computational Workflows with Continuous Analysis

Beaulieu-Jones, B. K., & Greene, C. S. (2016) · doi:10.1101/056473 · Cited by 154

Formal definition and implementation of reproducibility tenets for computational workflows

Pritchard, N., & Wicenec, A. J. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.107684 · Cited by 7

Data-Driven Framework for Aligning Artificial Intelligence with Inclusive Development in the Global South

Silva, G. H. B. A. D. (2025) · Sustainability · doi:10.3390/su17219360 · Cited by 6

Accessibility by Design: A Systematic Review of Inclusive E-Book Standards, Tools, and Practices

Silva, L. C. E., Pimentel, B. A., da Costa, B. J. D., Filho, R. S. E., Sousa, L., da Cruz, N. J. T., & Silva, R. D. A. (2025) · Sustainability · doi:10.3390/su172411173 · Cited by 6

Overcoming barriers to reproducibility in geoscientific data analysis: Challenges and practical implementation strategies

Schlögl, M., Waltersdorfer, L., Regner, P., Siposova, A., & Brenning, A. (2026) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2026.106962 · Cited by 6

Numerical Modeling of Debris Flows: A Conceptual Assessment

Iverson, R. M., & George, D. L. (2024) · Geoenvironmental disaster reduction · doi:10.1007/978-3-031-48691-3_5 · Cited by 5

The Case for Open Source Software: The Interactional Discourse Lab

Choi, S. (2015) · Applied Linguistics · doi:10.1093/applin/amv066 · Cited by 5

End-User Programmers Repurposing End-User Programming Tools to Foster Diversity in Adult End-User Programming Education

Kross, S., & Guo, P. J. (2019) · IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) · doi:10.1109/vlhcc.2019.8818824 · Cited by 4

The Science of Science

Wang, D., & Liu, L. (2020) · ACM/IEEE Joint Conference on Digital Libraries · doi:10.1145/3383583.3398500 · Cited by 8

Positive and Negative Contributions of XPS to Reproducibility Issues

Baer, D. R., & Engelhard, M. (2019) · Journal of Surface Analysis · doi:10.1384/jsa.26.94 · Cited by 5

Opportunities for Adopting Open Research Data in Learning Analytics

Biernacka, K., & Niels Pinkwart, C. (2021) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-7998-7103-3.ch002 · Cited by 5

Active Maintenance: A Proposal for the Long-Term Computational Reproducibility of Scientific Results

Peer, L., Orr, L., & Coppock, A. (2021) · PS Political Science & Politics · doi:10.1017/s1049096521000366 · Cited by 5

A Primer into the Current State of Artificial Intelligence in Gastroenterology

Moldoveanu, A. C., & Fierbinteanu-Braticevici, C. G. (2022) · Journal of Gastrointestinal and Liver Diseases · doi:10.15403/jgld-4180 · Cited by 5

Mitigation Strategies to Improve Reproducibility of Poverty Estimations From Remote Sensing Images Using Deep Learning

Machicao, J., Abbes, A. B., Meneguzzi, L., Corrêa, P. L. P., Specht, A., David, R., Subsol, G., Vellenich, D. F., Devillers, R., Stall, S., et al. (2022) · Earth and Space Science · doi:10.1029/2022ea002379 · Cited by 8

TIER2: enhancing Trust, Integrity and Efficiency in Research through next-level Reproducibility

Ross‐Hellauer, T., Klebel, T., Bannach‐Brown, A., Horbach, S. P. J. M., Jabeen, H., Manola, N., Metodiev, T., Papageorgiou, H., Reczko, M., Sansone, S., et al. (2022) · Research Ideas and Outcomes · doi:10.3897/rio.8.e98457 · Cited by 5

Reproducibility Debt: Challenges and Future Pathways

Hassan, Z., Treude, C., Norrish, M., Williams, G., & Potanin, A. (2024) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3663529.3663778 · Cited by 5

Who cares about agriculture? Analyzing German parliamentary debates on agriculture and food with structural topic modeling

Mennig, P. (2024) · Food Policy · doi:10.1016/j.foodpol.2024.102788 · Cited by 5

Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI

Moulton, R. H., McCully, G. A., & Hastings, J. D. (2024) · Cyber Awareness and Research Symposium (CARS) · doi:10.1109/cars61786.2024.10778911 · Cited by 5

MINRES-QLP Pack and Reliable Reproducible Research via Supportable Scientific Software

Choi, S.-C. T. (2014) · Journal of Open Research Software · doi:10.5334/jors.bb · Cited by 5

Platforms for publishing and archiving computer-aided research

Hinsen, K. (2014) · F1000Research · doi:10.12688/f1000research.5773.1 · Cited by 5

Epidemiology, Austerity, and Innovation

Samet, J. M., & Ness, R. B. (2012) · American Journal of Epidemiology · doi:10.1093/aje/kws035 · Cited by 5

Reporting on European forest fragmentation: Standardised indices and web map services

Christine, E., Caudullo, G., DANIELE, D. R., Whitmore, C., & JESUS, S.-M.-A. (2012) · Joint Research Centre (European Commission) · Cited by 5

ABC

Apaolaza, A., Haines, R., Aizpurua, A., Brown, A. J., Evans, M., Jolly, S., Harper, S., & Jay, C. (2016) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/2851581.2892483 · Cited by 5

repo: an R package for data-centered management of bioinformatic pipelines

Napolitano, F. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1510-6 · Cited by 5

Train the Trainers: Medical Technology for the Sustainable Development of Africa

Ruiz‐Alzola, J., Skareb, A., Idriss, A. M., Diao, B., Ferreira, J. D. R. D. P., Rodrigues, M. A. F., Rivero, L. L., & Kikinis, R. (2018) · IEEE Global Humanitarian Technology Conference (GHTC) · doi:10.1109/ghtc.2018.8601677 · Cited by 5

Fuzzy Systems-as-a-Service in Cloud Computing

Parra-Royón, M., & Benítez, J. M. (2019) · International Journal of Computational Intelligence Systems · doi:10.2991/ijcis.d.190912.001 · Cited by 5

Reproducibility by Other Means: Transparent Research Objects

McPhillips, T., Willis, C., Gryk, M. R., Núñez-Corrales, S., & Ludäscher, B. (2019) · International Conference on e-Science · doi:10.1109/escience.2019.00066 · Cited by 5

Beyond first-person shooter video games: Using computational modeling and simulation of mass violence for threat assessment and management.

Briggs, T. W., & Pollard, J. W. (2019) · Journal of Threat Assessment and Management · doi:10.1037/tam0000128 · Cited by 5

Coupling spectral imaging and laboratory analyses to digitally map sediment parameters and stratigraphic layers in Yeha, Ethiopia

Haburaj, V., Japp, S., Gerlach, I., Hoelzmann, P., & Schütt, B. (2020) · PLoS ONE · doi:10.1371/journal.pone.0238894 · Cited by 5

DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

Ghannoum, S., Netto, W. L., Fantini, D., Ragan-Kelley, B., Parizadeh, A., Jonasson, E., Ståhlberg, A., Farhan, H., & Köhn‐Luque, A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22031399 · Cited by 5

On the reproducibility of fully convolutional neural networks for modeling time–space-evolving physical systems

Pinto, W. G., Alguacil, A., & Bauerheim, M. (2022) · Data-Centric Engineering · doi:10.1017/dce.2022.18 · Cited by 5

Common-sense approaches to sharing tabular data alongside publication

Tierney, N. J., & Ram, K. (2021) · Patterns · doi:10.1016/j.patter.2021.100368 · Cited by 5

Wailord: Parsers and Reproducibility for Quantum Chemistry

Goswami, R. R. (2022) · Proceedings of the Python in Science Conferences · doi:10.25080/majora-212e5952-021 · Cited by 5

Multi-level parallel multi-layer block reproducible summation algorithm

Li, K., He, K., Graillat, S., Jiang, H., Gu, T.-X., & Liu, J. (2023) · Parallel Computing · doi:10.1016/j.parco.2023.102996 · Cited by 5

Guidelines for systematic reporting of sequence alignments

Vihinen, M. (2020) · Biology Methods and Protocols · doi:10.1093/biomethods/bpaa001 · Cited by 5

UiLab, a Workbench for Conducting and Reproducing Experiments in GUI Visual Design

Burny, N., & Vanderdonckt, J. M. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3457143 · Cited by 5

Comment on: “Desideratum for Evidence-Based Epidemiology”

Hennessy, S., & Leonard, C. E. (2014) · Drug Safety · doi:10.1007/s40264-014-0252-x · Cited by 6

Empirical estimates suggest most published medical research is truePreprint

Jager, L. R., & Leek, J. T. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1301.3718 · Cited by 5

Towards Recommender Engineering: tools and experiments for identifying recommender differences

Ekstrand, M. D. (2014) · University of Minnesota Digital Conservancy (University of Minnesota) · Cited by 5

The Invisible Water Utility. Employee Behaviour and Customer Experience in Service-Dominant LogicPreprint

Prevos, P. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2979902 · Cited by 5

An open source web application for distributed geospatial data exploration

Curry, P. A., & Moosdorf, N. (2019) · Scientific Data · doi:10.1038/sdata.2019.14 · Cited by 5

Elements and Principles of Data AnalysisPreprint

Hicks, S. C., & Peng, R. D. (2019) · arXiv (Cornell University) · Cited by 5

Elements and Principles for Characterizing Variation between Data AnalysesPreprint

Hicks, S. C., & Peng, R. D. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.07639 · Cited by 5

A Survey on Reproducibility by Evaluating Deep Reinforcement Learning Algorithms on Real-World RobotsPreprint

Lynnerup, N. A., Nolling, L., Andersen, R. H., & Hallam, J. C. T. (2019) · University of Southern Denmark Research Portal (University of Southern Denmark) · doi:10.48550/arxiv.1909.03772 · Cited by 6

[Vagal effect on sino-atrial node frequency and A-V overdrive in hypersensitive carotid sinus reflex and sick sinus syndrome].

Schwarz, F., Thormann, J., & Zimmermann, H. (1975) · PubMed · Cited by 5

Training Data: How can we best prepare instructors to teach data science in undergraduate biology and environmental science courses?Preprint

Emery, N. C., Crispo, E., Supp, S. R., Kerkhoff, A. J., Farrell, K. J., Bledsoe, E. K., O’Donnell, K., McCall, A. C., & Aiello‐Lammens, M. E. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.25.428169 · Cited by 5

Numerical modeling of Earth's dynamic surface: a community approachPreprint

Tucker, G. E., Hutton, E. W. H., Piper, M. D., Campforts, B., Gan, T., Barnhart, K. R., Kettner, A. J., Overeem, I., Peckham, S. D., McCready, L., et al. (2021) · doi:10.31223/x51615 · Cited by 5

DRT: A new toolbox for the Standard EEG Data Structure in large-scale EEG applications

Dong, L., Zhang, Y., Zhao, L., Zheng, T., Wang, W., Li, J., Gong, D., Liu, T., & Yao, D. (2021) · SoftwareX · doi:10.1016/j.softx.2021.100933 · Cited by 5

Machine learning-based evidence and attribution mapping of 100,000 climate impact studiesPreprint

Callaghan, M., Schleussner, C., Nath, S., Lejeune, Q., Knutson, T. R., Reichstein, M., Hansen, G., Theokritoff, E., Andrijevic, M., Brecha, R. J., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-783398/v1 · Cited by 5

Traditional and contemporary approaches to mathematical fitness-fatigue models in exercise science: A practical guide with resources. Part I.Preprint

Hemingway, B. S., Greig, L., Jovanovic, M., Ogorek, B., & Swinton, P. A. (2020) · doi:10.31236/osf.io/ap75j · Cited by 5

playOmics: A multi-omics pipeline for interpretable predictions and biomarker discoveryPreprint

Głowacka‐Walas, J., Sijko, K., Wojdan, K., & Gambin, T. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.12.584088 · Cited by 5

A retrospective analysis of 400 publications reveals patterns of irreplicability across an entire life sciences research fieldPreprint

Lemaitre, J. C., Popelka, D., Ribotta, B., Westlake, H. E., Chakrabarti, S., Li, X., Hanson, M. A., Jiang, H., Cara, F. D., Kurant, E., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.07.663460 · Cited by 5

Evaluating the performance of ChatGPT-5, Claude, and DeepSeek for statistical analysis in medicine

Sebo, P., & Wang, T. (2026) · Internal and Emergency Medicine · doi:10.1007/s11739-026-04291-4 · Cited by 4

From tool to collaborator: rethinking GIScience as GIS becomes agentic and autonomous

Kazazi, A. K., & Li, Z. (2026) · International Journal of Digital Earth · doi:10.1080/17538947.2026.2687228 · Cited by 4

Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflows

Bayarri, G., Andrio, P., Gelpí, J. L., & Orozco, M. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012173 · Cited by 4

Empirical behaviour of Anselin et al.’s locally robust LM tests for spatial dependence in a panel data setting

Millo, G. (2025) · Regional Science and Urban Economics · doi:10.1016/j.regsciurbeco.2025.104106 · Cited by 4

Physics-Informed Multi-Task Neural Network (PINN) Learning for Ultra-High-Performance Concrete (UHPC) Strength Prediction

Yan, L., Liu, P., Yao, Y., Yang, F., & Xu, F. (2025) · Buildings · doi:10.3390/buildings15234243 · Cited by 4

Scientific software development in the AI era: reproducibility, MLOps, and applications in soft matter physics

Cheimarios, N. (2025) · Frontiers in Physics · doi:10.3389/fphy.2025.1711356 · Cited by 4

The Knowledge-Remixing Bottleneck

Groth, P. (2013) · IEEE Intelligent Systems · doi:10.1109/mis.2013.138 · Cited by 4

Reusable, extensible, and modifiable R scripts and Kepler workflows for comprehensive single set ChIP-seq analysis

Cormier, N. J. A., Kolisnik, T., & Bieda, M. C. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1125-3 · Cited by 4

Social Big Data: Concepts and Theory

Ishikawa, H., & Yamamoto, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-662-62919-2_3 · Cited by 4

A software environment for effective reliability management for pulsed power design

Robinson, A. C., Drake, R., Swan, M. S., Bennett, N., Smith, T. M., Hooper, R. W., & Laity, G. (2021) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2021.107580 · Cited by 4

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