Evidence map›Paper›PMID 39364207›Full record

ArticleQuantitative biology (Beijing, China)2024

Bioinformatics and biomedical informatics with ChatGPT: Year one review.

Jinge Wang, Zien Cheng, Qiuming Yao, Li Liu, Dong Xu, Gangqing Hu

Abstract read
In one paragraph

Article in Quantitative biology (Beijing, China), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Longitudinal big biological data in the AI era.Molecular systems biology · 2025
    Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Foundation models for bioinformatics.Quantitative biology (Beijing, China) · 2024
    Article
  14. Article
  15. Review
  16. Article
  17. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Jinge WangDepartment of Microbiology, Immunology & Cell Biology, West Virginia University, Morgantown, West Virginia, USA.
Zien ChengDepartment of Microbiology, Immunology & Cell Biology, West Virginia University, Morgantown, West Virginia, USA.
Qiuming YaoSchool of Computing, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
Li LiuCollege of Health Solutions, Arizona State University, Phoenix, Arizona, USA.
Dong XuDepartment of Electrical Engineer and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, Missouri, USA.
Gangqing HuDepartment of Microbiology, Immunology & Cell Biology, West Virginia University, Morgantown, West Virginia, USA.

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Sally Lynn Hodder · 2012 to 2026
$81.0M
WV INBRE: The Inhibitor of Growth Family Member 4 (ING4) inhibits L-Type Amino Acid Transporter 1 (LAT1) expression to suppress Breast CancerP20GM103434 · NIGMS · MARSHALL UNIVERSITY · PI GARY O RANKIN · 2012 to 2026
$61.1M
Interdisciplinary Systems-based Training for Precision NutritionT32DK137525 · NIDDK · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI Li Liu, Corrie Marie Whisner · 2023 to 2026
$1.4M
Image-guided Biocuration of Disease Pathways From Scientific LiteratureR01LM013392 · NLM · UNIVERSITY OF MISSOURI-COLUMBIA · PI POPESCU, MIHAIL · 2020 to 2023
$1.3M
Discover and Analyze Germline-Somatic Interactions in CancerR01LM013438 · NLM · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI LIU, LI, YANG, PING · 2021 to 2023
$1.0M
NIDDK NIH HHS T32 DK137525NIGMS NIH HHS P20 GM103434NIGMS NIH HHS U54 GM104942NLM NIH HHS R01 LM013392NLM NIH HHS R01 LM013438
6 · The paper itself

Abstract

The year 2023 marked a significant surge in the exploration of applying large language model chatbots, notably Chat Generative Pre-trained Transformer (ChatGPT), across various disciplines. We surveyed the application of ChatGPT in bioinformatics and biomedical informatics throughout the year, covering omics, genetics, biomedical text mining, drug discovery, biomedical image understanding, bioinformatics programming, and bioinformatics education. Our survey delineates the current strengths and limitations of this chatbot in bioinformatics and offers insights into potential avenues for future developments.

Indexed as

bioinformaticsbiomedical informaticsChatGPT

Identifiers

PMID39364207
PMCPMC11446534

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.