ArticlePLoS computational biology2020
Ten simple rules for making training materials FAIR.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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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
25 citing papers in PubMed.
- Therapies for Heart Failure: Clinical Updates and Perspectives.Journal of clinical medicine · 2026Article
- Training resources on open and responsible research and innovation (Open RRI): gaps, quality and opportunities to advance training.Open research Europe · 2026Article
- Leveraging training expertise to build capacity in computational personalised medicine.Bioinformatics advances · 2026Article
- Challenges in bioinformatics education courses organization.Biophysical reviews · 2025Review
- Ten simple rules for training by researchers for researchers in a rapidly evolving workforce.PLoS computational biology · 2025Article
- Ten quick tips for navigating intellectual property in FAIR educational resources.PLoS computational biology · 2025Article
- Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction.GigaByte (Hong Kong, China) · 2025Article
- Making bioinformatics training FAIR: the EMBL-EBI training portal.Frontiers in bioinformatics · 2024Article
- A research data management (RDM) community for ELIXIR.F1000Research · 2024Article
- From the establishment of a national bioinformatics society to the development of a national bioinformatics infrastructure.F1000Research · 2024Article
- Using Glittr.org to find, compare and re-use online materials for training and education.PloS one · 2024Article
- Bioschemas training profiles: A set of specifications for standardizing training information to facilitate the discovery of training programs and resources.PLoS computational biology · 2023Article
- Galaxy Training: A powerful framework for teaching!PLoS computational biology · 2023Article
- Training Infrastructure as a Service.GigaScience · 2022Article
- Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan.PLoS computational biology · 2022Article
- Ten simple rules for improving research data discovery.PLoS computational biology · 2022Article
- Collections Education: The Extended Specimen and Data Acumen.Bioscience · 2022Article
- The European Bioinformatics Institute (EMBL-EBI) in 2021.Nucleic acids research · 2022Article
- Ten simple rules for researchers who want to develop web apps.PLoS computational biology · 2022Article
- Trainingspace: Neuroeducation Without Borders.Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Everything we do today is becoming more and more reliant on the use of computers. The field of biology is no exception; but most biologists receive little or no formal preparation for the increasingly computational aspects of their discipline. In consequence, informal training courses are often needed to plug the gaps; and the demand for such training is growing worldwide. To meet this demand, some training programs are being expanded, and new ones are being developed. Key to both scenarios is the creation of new course materials. Rather than starting from scratch, however, it's sometimes possible to repurpose materials that already exist. Yet finding suitable materials online can be difficult: They're often widely scattered across the internet or hidden in their home institutions, with no systematic way to find them. This is a common problem for all digital objects. The scientific community has attempted to address this issue by developing a set of rules (which have been called the Findable, Accessible, Interoperable and Reusable [FAIR] principles) to make such objects more findable and reusable. Here, we show how to apply these rules to help make training materials easier to find, (re)use, and adapt, for the benefit of all.
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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.