Evidence map›Paper›PMID 40985030›Full record

ArticlePeerJ2025

Fine-tuning protein language models unlocks the potential of underrepresented viral proteomes.

Rajan Sawhney, Barbra D Ferrell, Thibaut Dejean, Zachary Schreiber, William Harrigan, Shawn W Polson, K Eric Wommack, Mahdi Belcaid

Abstract read
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Machine Learning-Based Characterization ofPathogens (Basel, Switzerland) · 2025
    Article
  8. Mechanistic modeling or machine learning for detecting variants of concern: Why not both?Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Rajan SawhneyDepartment of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, Hawai'i, United States of America.
Barbra D FerrellDepartment of Computer and Information Sciences, University of Delaware, Newark, DE, United States of America.
Thibaut DejeanDepartment of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, Hawai'i, United States of America.
Zachary SchreiberDepartment of Computer and Information Sciences, University of Delaware, Newark, DE, United States of America.
William HarriganHawai'i Institute of Marine Biology, University of Hawaii at Manoa, Honolulu, Hawai'i, United States of America.
Shawn W PolsonDepartment of Computer and Information Sciences, University of Delaware, Newark, DE, United States of America.
K Eric WommackDelaware Biotechnology Institute, University of Delaware, Newark, DE, United States of America.
Mahdi BelcaidDepartment of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, Hawai'i, United States of America.

Funding

Predictive Modeling & Optimal Control Framework for Model-Based Epidemic Response in DelawareP20GM103446 · NIGMS · UNIVERSITY OF DELAWARE · PI Shawn W Polson · 2012 to 2026
$67.2M
Data Management and Storage System for Shared Resource FacilitiesS10OD028725 · OD · UNIVERSITY OF DELAWARE · PI POLSON, SHAWN W · 2021 to 2021
$600k
NIGMS NIH HHS P20 GM103446NIH HHS S10 OD028725
6 · The paper itself

Abstract

Protein language models (pLMs) have revolutionized computational biology by generating rich protein vector representations, or embeddings-enabling major advancements in

Indexed as

Computational BiologyProteomeViral ProteinsVirusesProteomeViral ProteinsArtificial IntelligenceProtein Language ModelsProteomicsViruses

Identifiers

PMID40985030
PMCPMC12450373

What OpenQuestion holds

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LicenceCC BY
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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.