Evidence map›Paper›PMID 21331885›Full record

ReviewVirologica Sinica2011

Advances of bioinformatics tools applied in virus epitopes prediction.

Ping Chen, Simon Rayner, Kang-Hong Hu

Abstract readReview
In one paragraph

Review in Virologica Sinica, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Predicting alloreactivity in transplantation.Journal of immunology research · 2014
    Review
  11. Article
  12. Article
  13. 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

3 authors.

Ping ChenState Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China.
Simon Rayner
Kang-Hong Hu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the in silico epitopes prediction tools have facilitated the progress of vaccines development significantly and many have been applied to predict epitopes in viruses successfully. Herein, a general overview of different tools currently available, including T cell and B cell epitopes prediction tools, is presented. And the principles of different prediction algorithms are reviewed briefly. Finally, several examples are present to illustrate the application of the prediction tools.

Indexed as

AlgorithmsComputational BiologyEpitopesEpitopes, B-LymphocyteEpitopes, T-LymphocyteVirusesEpitopesEpitopes, B-LymphocyteEpitopes, T-Lymphocyte

Identifiers

PMID21331885
PMCPMC7090880

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.