Evidence map›Paper›PMID 40000215›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2024

[Prediction of MHC II antigen peptide-T cell receptors binding based on foundation model].

Minrui Xu, Siwen Zhang, Manman Lu, Yuan Gao, Menghuan Zhang, Yong Lin, Lu Xie

Abstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

7 authors.

Minrui XuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China.
Siwen ZhangShanghai Institute for Biomedical and Pharmaceutical Technologies, Fudan University, Shanghai 200237, P. R. China.
Manman LuShanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, P. R. China.
Yuan GaoSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China.
Menghuan ZhangSchool of Life Science and Technology, Tongji University, Shanghai 200092, P. R. China.
Yong LinSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China.
Lu XieShanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The specific binding of T cell receptors (TCRs) to antigenic peptides plays a key role in the regulation and mediation of the immune process and provides an essential basis for the development of tumour vaccines. In recent years, studies have mainly focused on TCR prediction of major histocompatibility complex (MHC) class I antigens, but TCR prediction of MHC class II antigens has not been sufficiently investigated and there is still much room for improvement. In this study, the combination of MHC class II antigen peptide and TCR prediction was investigated using the ProtT5 grand model to explore its feature extraction capability. In addition, the model was fine-tuned to retain the underlying features of the model, and a feed-forward neural network structure was constructed for fusion to achieve the prediction model. The experimental results showed that the method proposed in this study performed better than the traditional methods, with a prediction accuracy of 0.96 and an AUC of 0.93, which verifies the effectiveness of the model proposed in this paper.

Indexed as

Histocompatibility Antigens Class IIPeptidesReceptors, Antigen, T-CellHumansNeural Networks, ComputerProtein BindingHistocompatibility Antigens Class IIPeptidesReceptors, Antigen, T-CellFoundation modelImmunotherapyPrediction of MHC Ⅱ antigen peptide-T cell receptors bindingProtT5 model

Identifiers

PMID40000215
PMCPMC11955369

What OpenQuestion holds

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Registered trials

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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.