Evidence map›Paper›PMID 27479659›Full record

ArticleCurrent protocols in immunology2016

TepiTool: A Pipeline for Computational Prediction of T Cell Epitope Candidates.

Sinu Paul, John Sidney, Alessandro Sette, Bjoern Peters

Abstract read
In one paragraph

Article in Current protocols in immunology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers.

0numbers the graph read from it
0cells of the map it votes in
168citing 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

168 citing papers in PubMed.

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108 more citing papers are in PubMed but not listed here.

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.

Sinu PaulLa Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, California.
John SidneyLa Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, California.
Alessandro SetteLa Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, California.
Bjoern PetersLa Jolla Institute for Allergy and Immunology, Division of Vaccine Discovery, La Jolla, California.

Funding

NIAID NIH HHS HHSN272201200010C
6 · The paper itself

Abstract

Computational prediction of T cell epitope candidates is currently being used in several applications including vaccine discovery studies, development of diagnostics, and removal of unwanted immune responses against protein therapeutics. There have been continuous improvements in the performance of MHC binding prediction tools, but their general adoption by immunologists has been slow due to the lack of user-friendly interfaces and guidelines. Current tools only provide minimal advice on what alleles to include, what lengths to consider, how to deal with homologous peptides, and what cutoffs should be considered relevant. This protocol provides step-by-step instructions with necessary recommendations for prediction of the best T cell epitope candidates with the newly developed online tool called TepiTool. TepiTool, which is part of the Immune Epitope Database (IEDB), provides some of the top MHC binding prediction algorithms for number of species including humans, chimpanzees, bovines, gorillas, macaques, mice, and pigs. The TepiTool is freely accessible at http://tools.iedb.org/tepitool/. © 2016 by John Wiley & Sons, Inc.

Indexed as

SoftwareAlgorithmsAllelesAnimalsBiological TherapyCattleComputational BiologyEpitope MappingEpitopes, T-LymphocyteHistocompatibility Antigens Class IHumansMicePeptidesSwineVaccinesEpitopes, T-LymphocyteHistocompatibility Antigens Class IPeptidesVaccinesbinding affinity predictionCTL epitope predictionMHC class IMHC class IIT cell epitope

Identifiers

PMID27479659
PMCPMC4981331

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.