Evidence map›Paper›PMID 41816779›Full record

ArticleNAR genomics and bioinformatics2026

Eduomics: a Nextflow pipeline to simulate -omics data for education.

Lorenzo Sola, Davide Bagordo, Simone Carpanzano, Mariangela Santorsola, Francesco Lescai

Erratum issuedAbstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Lorenzo SolaDepartment of Biology and Biotechnology "L. Spallazani", University of Pavia, Pavia, IT-27100, Italy.
Davide BagordoDepartment of Biology and Biotechnology "L. Spallazani", University of Pavia, Pavia, IT-27100, Italy.
Simone CarpanzanoDepartment of Biology and Biotechnology "L. Spallazani", University of Pavia, Pavia, IT-27100, Italy.
Mariangela SantorsolaDepartment of Biology and Biotechnology "L. Spallazani", University of Pavia, Pavia, IT-27100, Italy.
Francesco LescaiDepartment of Biology and Biotechnology "L. Spallazani", University of Pavia, Pavia, IT-27100, Italy.ORCID https://orcid.org/0000-0002-6399-9101

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bridging the gap between learning algorithms and biological interpretation remains the central challenge of bioinformatics education. To move students beyond just learning code and acquire higher-order knowledge, educators face a complexity overload when attempting to design realistic learning experiences. Simulating realistic data forces educators to master different tools and dependencies. Existing simulators are built for benchmarking and lack the narrative context essential for teaching interpretation; this limitation prevents a shift from problem-solving to what we believe should be an immersive 'storyline-based learning'. Eduomics facilitates massive scaling: educators can generate hundreds of unique, validated datasets for assessments or tutoring in a matter of hours. By removing barriers to adoption and embedding raw data within a rich clinical context, eduomics offers an accessible, scalable solution to truly innovate bioinformatics education. Eduomics facilitates massive scaling: educators can generate hundreds of unique, validated datasets for assessments or tutoring in a matter of hours. By removing barriers to adoption and embedding raw data within a rich clinical context, eduomics offers an accessible, scalable solution to truly innovate bioinformatics education.

Indexed as

Computational BiologyAlgorithmsComputer SimulationHumansSoftware

Identifiers

PMID41816779
PMCPMC12972896

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.