ArticleF1000Research2017
Four simple recommendations to encourage best practices in research software.
Article in F1000Research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses 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
52 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Assessment of the functionality and usability of open-source rare variant analysis pipelines.Briefings in bioinformatics · 2025Pooled it
- Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software.Metabolomics : Official journal of the Metabolomic Society · 2023Pooled it
- Ten quick tips to SNIFF out sustainable and secure scientific software.PLoS computational biology · 2026Article
- Journal research data policies in materials science.Digital discovery · 2026Review
- Informatics at the Frontier of Cancer Research.Cancer research · 2025Review
- Open-Source and FAIR Research Software for Proteomics.Journal of proteome research · 2025Review
- HTSinfer: inferring metadata from bulk Illumina RNA-Seq libraries.Bioinformatics (Oxford, England) · 2025Article
- Navigating the Multiverse: a Hitchhiker's guide to selecting harmonization methods for multimodal biomedical data.Biology methods & protocols · 2025Review
- A how-to guide for code sharing in biology.PLoS biology · 2024Review
- FAIRsoft-a practical implementation of FAIR principles for research software.Bioinformatics (Oxford, England) · 2024Article
- Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios.Genome biology · 2024Article
- A multi-omics data analysis workflow packaged as a FAIR Digital Object.GigaScience · 2024Article
- Article
- Strategic priorities and challenges in research software funding: Results from an international survey.F1000Research · 2024Article
- A research data management (RDM) community for ELIXIR.F1000Research · 2024Article
- A primer on correlation-based dimension reduction methods for multi-omics analysis.Journal of the Royal Society, Interface · 2023Review
- Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool.Scientific data · 2023Article
- Open Science Drone Toolkit: Open source hardware and software for aerial data capture.PloS one · 2023Article
- The ELIXIR Biodiversity Community: Understanding short- and long-term changes in biodiversity.F1000Research · 2023Article
- Ten simple rules for using public biological data for your research.PLoS computational biology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
49 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Scientific research relies on computer software, yet software is not always developed following practices that ensure its quality and sustainability. This manuscript does not aim to propose new software development best practices, but rather to provide simple recommendations that encourage the adoption of existing best practices. Software development best practices promote better quality software, and better quality software improves the reproducibility and reusability of research. These recommendations are designed around Open Source values, and provide practical suggestions that contribute to making research software and its source code more discoverable, reusable and transparent. This manuscript is aimed at developers, but also at organisations, projects, journals and funders that can increase the quality and sustainability of research software by encouraging the adoption of these recommendations.
Indexed as
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.