Evidence map›Paper›PMID 42185516›Full record

ReviewNPJ digital medicine2026

Rethinking bioinformatics expertise in the era of artificial intelligence.

Wilson Wen Bin Goh, Annikka Polster, Limsoon Wong, Marija Cvijovic

Abstract readReview
In one paragraph

Review in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Wilson Wen Bin Goh *Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, Singapore.
Annikka Polster *Chalmers University of Technology, Department of Life, Gothenburg, Sweden.
Limsoon WongSchool of Computing, National University of Singapore, 13 Computing Drive, Singapore, Singapore.
Marija CvijovicUniversity of Gothenburg, Department of Mathematical Sciences, Gothenburg, Sweden. marija.cvijovic@chalmers.se.

Funding

Adlerbert Research Foundation 2024-899Ministry of Education (MOE), Singapore Tier 1 grant RS08/21MOE Tier 2 grant MOE-T2EP20221-0005MOE Tier 3 grant MOE-MOET32021-0004/-0007Stiftelsen för Strategisk Forskning SAB19-0011Swedish Research Council VR2023-04319
6 · The paper itself

Abstract

Artificial intelligence (AI) is often framed as replacing scientific expertise, especially in bioinformatics. We argue instead that AI is a powerful accelerant whose value depends on expert guidance in design, data curation, interpretation, and governance. Because AI cannot judge biological meaning or verify scientific validity, bioinformaticians remain essential. Their role is shifting from workflow execution toward AI design, complex discovery, and responsible institutional leadership across research, translation, and clinical practice.

Identifiers

PMID42185516
PMCPMC13201767

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.