Evidence map›Paper›PMID 39284801›Full record

ArticleNature communications2024

ENCORE: a practical implementation to improve reproducibility and transparency of computational research.

Antoine H C van Kampen, Utkarsh Mahamune, Aldo Jongejan, Barbera D C van Schaik, Daria Balashova, Danial Lashgari, Mia Pras-Raves, Eric J M Wever, Adrie D Dane, Rodrigo García-Valiente and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Antoine H C van Kampen *Amsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands. a.h.vankampen@amsterdamumc.nl.ORCID http://orcid.org/0000-0003-1025-7232
Utkarsh Mahamune *Amsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.
Aldo JongejanAmsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-8948-2549
Barbera D C van SchaikAmsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-5568-8127
Daria BalashovaAmsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.
Danial LashgariAmsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-8748-2414
Mia Pras-RavesAmsterdam UMC, University of Amsterdam, Department of Clinical Chemistry, Laboratory Genetic Metabolic Diseases, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-5624-8094
Eric J M WeverAmsterdam UMC, University of Amsterdam, Department of Clinical Chemistry, Laboratory Genetic Metabolic Diseases, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-2116-507X
Adrie D DaneAmsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-6322-8083
Rodrigo García-ValienteAmsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0003-0444-5587
Perry D MoerlandAmsterdam UMC, University of Amsterdam, Bioinformatics Laboratory, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-2357-3659

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions) 765158EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions) 847551Innovative Medicines Initiative (IMI) 831434
6 · The paper itself

Abstract

Reproducibility of computational research is often challenging despite established guidelines and best practices. Translating these guidelines into practical applications remains difficult. Here, we present ENCORE, an approach to enhance transparency and reproducibility by guiding researchers in how to structure and document a computational project. ENCORE builds on previous efforts in computational reproducibility and integrates all project components into a standardized file system structure. It utilizes pre-defined files as documentation templates, leverages GitHub for software versioning, and includes an HTML-based navigator. ENCORE is designed to be agnostic to the type of computational project, data, programming language, and ICT infrastructure, and does not rely on specific software tools. We also share our group's experience using ENCORE, highlighting that the most significant challenge to the routine adoption of approaches like ours is the lack of incentives to motivate researchers to dedicate sufficient time and effort to ensure reproducibility.

Identifiers

PMID39284801
PMCPMC11405857

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.