Evidence map›Paper›PMID 23970944›Full record

ReviewComputational and mathematical methods in medicine2013

Bioinformatics resources and tools for conformational B-cell epitope prediction.

Pingping Sun, Haixu Ju, Zhenbang Liu, Qiao Ning, Jian Zhang, Xiaowei Zhao, Yanxin Huang, Zhiqiang Ma, Yuxin Li

Abstract readReview
In one paragraph

Review in Computational and mathematical methods in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Improving B-cell epitope prediction.Drug discovery today · 2025
    Review
  5. Article
  6. Article
  7. Deep learning of antibody epitopes using positional permutation vectors.Computational and structural biotechnology journal · 2024
    Article
  8. Article
  9. Article
  10. Review
  11. Genomic comparison betweenFrontiers in veterinary science · 2024
    Article
  12. Article
  13. Multi-perspectives and challenges in identifying B-cell epitopes.Protein science : a publication of the Protein Society · 2023
    Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Saudi journal of biological sciences · 2022
    Article
  20. 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

9 authors.

Pingping SunSchool of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China.
Haixu Ju
Zhenbang Liu
Qiao Ning
Jian Zhang
Xiaowei Zhao
Yanxin Huang
Zhiqiang Ma
Yuxin Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of epitopes which invoke strong humoral responses is an essential issue in the field of immunology. Localizing epitopes by experimental methods is expensive in terms of time, cost, and effort; therefore, computational methods feature for its low cost and high speed was employed to predict B-cell epitopes. In this paper, we review the recent advance of bioinformatics resources and tools in conformational B-cell epitope prediction, including databases, algorithms, web servers, and their applications in solving problems in related areas. To stimulate the development of better tools, some promising directions are also extensively discussed.

Indexed as

AlgorithmsAmino Acid SequenceBinding SitesComputational BiologyComputer SimulationDatabases, ProteinEpitopes, B-LymphocyteHumansInternetProtein ConformationSoftwareEpitopes, B-Lymphocyte

Identifiers

PMID23970944
PMCPMC3736542

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.