Evidence map›Paper›PMID 21047511›Full record

ArticleJournal of immunological methods2011

Prediction of epitopes using neural network based methods.

Claus Lundegaard, Ole Lund, Morten Nielsen

Abstract read
In one paragraph

Article in Journal of immunological methods, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 1 pooled it
–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

61 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Searching Epitope-Based Vaccines Using Bioinformatics Studies.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
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1 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

3 authors.

Claus LundegaardCenter for Biological Sequence Analysis, DTU Systems Biology, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. lunde@cbs.dtu.dk
Ole Lund
Morten Nielsen

Funding

NIAID NIH HHS HHSH266200400006C
6 · The paper itself

Abstract

In this paper, we describe the methodologies behind three different aspects of the NetMHC family for prediction of MHC class I binding, mainly to HLAs. We have updated the prediction servers, NetMHC-3.2, NetMHCpan-2.2, and a new consensus method, NetMHCcons, which, in their previous versions, have been evaluated to be among the very best performing MHC:peptide binding predictors available. Here we describe the background for these methods, and the rationale behind the different optimization steps implemented in the methods. We go through the practical use of the methods, which are publicly available in the form of relatively fast and simple web interfaces. Furthermore, we will review results obtained in actual epitope discovery projects where previous implementations of the described methods have been used in the initial selection of potential epitopes. Selected potential epitopes were all evaluated experimentally using ex vivo assays.

Indexed as

Neural Networks, ComputerAlgorithmsAllelesAmino Acid SequenceEpitope MappingEpitopes, T-LymphocyteHistocompatibility Antigens Class IHumansInternetModels, MolecularMolecular Sequence DataPeptidesEpitopes, T-LymphocyteHistocompatibility Antigens Class IPeptides

Identifiers

PMID21047511
PMCPMC3134633

What OpenQuestion holds

Textmetadata
LicenceTDM
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.