ArticleSource code for biology and medicine2013
Git can facilitate greater reproducibility and increased transparency in science.
Article in Source code for biology and medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
57 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software.Metabolomics : Official journal of the Metabolomic Society · 2023Pooled it
- Reproducibility in biomedical research.Nature medicine · 2026Review
- Local implementation of scalable malaria molecular surveillance in a low-resource setting: a North-South collaborative model.Malaria journal · 2026Article
- PASTA-4-PHT: a pipeline for automated security and technical audits for the personal health train.BMC medical informatics and decision making · 2026Article
- To Be FAIR: Theory Specification Needs an Update.Perspectives on psychological science : a journal of the Association for Psychological Science · 2026Article
- Implementing a Version Control Platform as an Interactive Educational Framework for Bioinformatics and Artificial Intelligence in Medicine.Journal of medical signals and sensors · 2026Article
- Affording reusable data: recommendations for researchers from a data-intensive project.Scientific data · 2025Article
- Article
- GitHub enables collaborative and reproducible laboratory research.PLoS biology · 2025Article
- Article
- ENCORE: a practical implementation to improve reproducibility and transparency of computational research.Nature communications · 2024Article
- A how-to guide for code sharing in biology.PLoS biology · 2024Review
- Nine quick tips for open meta-analyses.PLoS computational biology · 2024Article
- Article
- SciDataFlow: a tool for improving the flow of data through science.Bioinformatics (Oxford, England) · 2024Article
- A libraries reproducibility hackathon: connecting students to university research and testing the longevity of published code.F1000Research · 2024Article
- The five pillars of computational reproducibility: bioinformatics and beyond.Briefings in bioinformatics · 2023Article
- Article
- Reproducibility in the Social Sciences.Annual review of sociology · 2022Article
- Open science at the science-policy interface: bringing in the evidence?Health research policy and systems · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundReproducibility is the hallmark of good science. Maintaining a high degree of transparency in scientific reporting is essential not just for gaining trust and credibility within the scientific community but also for facilitating the development of new ideas. Sharing data and computer code associated with publications is becoming increasingly common, motivated partly in response to data deposition requirements from journals and mandates from funders. Despite this increase in transparency, it is still difficult to reproduce or build upon the findings of most scientific publications without access to a more complete workflow.
findingsVersion control systems (VCS), which have long been used to maintain code repositories in the software industry, are now finding new applications in science. One such open source VCS, Git, provides a lightweight yet robust framework that is ideal for managing the full suite of research outputs such as datasets, statistical code, figures, lab notes, and manuscripts. For individual researchers, Git provides a powerful way to track and compare versions, retrace errors, explore new approaches in a structured manner, while maintaining a full audit trail. For larger collaborative efforts, Git and Git hosting services make it possible for everyone to work asynchronously and merge their contributions at any time, all the while maintaining a complete authorship trail. In this paper I provide an overview of Git along with use-cases that highlight how this tool can be leveraged to make science more reproducible and transparent, foster new collaborations, and support novel uses.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.