Evidence map›Paper›PMID 38907901›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.

Jingcheng Wu, Jiaoyang Li, Shuqing Chen, Zhan Zhou

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. 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.

Jingcheng WuInstitute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Jiaoyang LiCollege of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
Shuqing ChenInstitute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Zhan ZhouInstitute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China. zhanzhou@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformatics prediction for tumor neoantigens has rapidly developed, focusing on the prediction of peptide-HLA binding affinity. In this chapter, we introduce a user-friendly tool named DeepHLApan, which utilizes deep learning techniques to predict neoantigens by considering both peptide-HLA binding affinity and immunogenicity. We provide the application of DeepHLApan, along with the source code, docker version, and web-server. These resources are freely available at https://github.com/zjupgx/deephlapan and http://pgx.zju.edu.cn/deephlapan/ .

Indexed as

Computational BiologyDeep LearningHLA AntigensPeptidesSoftwareAntigens, NeoplasmHumansNeoplasmsProtein BindingAntigens, NeoplasmHLA AntigensPeptidesCancer immunologyDeep learningHuman leukocyte antigenNeoantigenRecurrent neural network

Identifiers

PMID38907901

What OpenQuestion holds

Textmetadata
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.