Evidence map›Paper›PMID 37606436›Full record

ReviewAntibodies (Basel, Switzerland)2023

Recent Progress in Antibody Epitope Prediction.

Xincheng Zeng, Ganggang Bai, Chuance Sun, Buyong Ma

Abstract readReview
In one paragraph

Review in Antibodies (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Improving B-cell epitope prediction.Drug discovery today · 2025
    Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Unlocking the potential ofFrontiers in bioinformatics · 2025
    Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Peptide Antibodies: Current Status.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  20. 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

4 authors.

Xincheng ZengEngineering Research Center of Cell & Therapeutic Antibody (MOE), School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0009-0008-6552-3247
Ganggang BaiEngineering Research Center of Cell & Therapeutic Antibody (MOE), School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China.
Chuance SunEngineering Research Center of Cell & Therapeutic Antibody (MOE), School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China.
Buyong MaEngineering Research Center of Cell & Therapeutic Antibody (MOE), School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0002-7383-719X

Funding

National Natural Science Foundation of China 32171246Science and Technology Commission of Shanghai Municipality 21JC1403700
6 · The paper itself

Abstract

Recent progress in epitope prediction has shown promising results in the development of vaccines and therapeutics against various diseases. However, the overall accuracy and success rate need to be improved greatly to gain practical application significance, especially conformational epitope prediction. In this review, we examined the general features of antibody-antigen recognition, highlighting the conformation selection mechanism in flexible antibody-antigen binding. We recently highlighted the success and warning signs of antibody epitope predictions, including linear and conformation epitope predictions. While deep learning-based models gradually outperform traditional feature-based machine learning, sequence and structure features still provide insight into antibody-antigen recognition problems.

Indexed as

antibodyantibody designartificial intelligenceepitope

Identifiers

PMID37606436
PMCPMC10443277

What OpenQuestion holds

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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.