Evidence map›Paper›PMID 41988107›Full record

ArticleGigaByte (Hong Kong, China)2026

AI in practice: a multilingual survey of 2025 BioHackathon participants.

Nattawet Sriwichai, Lucas Feriau, Pumipat Tongyoo, Yukiko Noda, Hikaru Gyoji, Pitiporn Noisagul, Susumu Goto, David Steinberg, Chatarin Wangsanuwat

Abstract read
In one paragraph

Article in GigaByte (Hong Kong, China), 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

9 authors.

Nattawet SriwichaiCenter of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Thailand.
Lucas FeriauPENQE, Inc., Japan.
Pumipat TongyooCenter for Agricultural Biotechnology, Kasetsart University, Kamphaeng Saen Campus, Thailand.
Yukiko NodaPENQE, Inc., Japan.
Hikaru GyojiPENQE, Inc., Japan.
Pitiporn NoisagulCenter of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Thailand.
Susumu GotoResearch Organization of Information and Systems, Joint-Support Center for Data Science Research, Database Center for Life Science, Japan.
David SteinbergCamber, San Francisco, USA.
Chatarin WangsanuwatSiriraj Long-read Lab (Si-LoL), Medical Bioinformatics, Siriraj Genomics, Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand.ORCID https://orcid.org/0000-0001-8228-2387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This dataset arises from a multilingual survey of AI use among participants and community members in the DBCLS BioHackathon 2025 in Japan. The questionnaire, offered in English, Japanese, and Thai, asked about how often respondents use AI tools, what they use them for, obstacles they encounter, institutional support, satisfaction, and concerns. Additional items captured role, institution type, work country, and other demographics, totaling 105 responses. The dataset includes both raw anonymized responses and a cleaned, standardized English-only version suitable for quantitative analysis, along with the full questionnaire, a data dictionary for cleaned dataset, and a translation lookup table. Free-text answers were screened and redacted to remove URLs, names, and other potentially identifiable information. Together, these materials provide a community-level view of AI practice in genomics, bioinformatics, software development, and related areas, and can support work on AI adoption, policy, and methods for analyzing survey data on AI use in science.

Identifiers

PMID41988107
PMCPMC13077790

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.