Evidence map›Paper›PMID 28191711›Full record

ArticleMolecular nutrition & food research2017

Bioinformatic screening and detection of allergen cross-reactive IgE-binding epitopes.

Scott McClain

Open access · hybridAbstract read
In one paragraph

Article in Molecular nutrition & food research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.6field-weighted citation impact, top 19% of its field
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

15 citing papers in PubMed, 39 citations in OpenAlex.

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  15. AllerBase: a comprehensive allergen knowledgebase.Database : the journal of biological databases and curation · 2017
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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

1 author at 1 institution in 1 country.

Scott McClainSyngenta Crop Protection, LLC, Durham, NC, USA.
Syngenta (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein allergens can be related by cross-reactivity. Allergens that share relevant sequence can cross-react, those lacking sufficient similarity in their IgE antibody-binding epitopes do not cross-react. Cross-reactivity is based on shared epitopes that is based on shared sequence and higher level structure (charge and shape). Epitopes are important in predicting cross-reactivity potential and may provide the potential to establish criteria that identify homology among allergens. Selected allergen's IgE-binding epitope sequences were used to determine how the FASTA algorithm could be used to identify a threshold of significance. A statistical measure (expectation value, E-value) was used to identify a threshold specific to identifying cross-reactivity potential. Peanut Ara h 1 and Ara h 2, shrimp tropomyosin Pen a 1, and birch tree pollen allergen, Bet v 1 were sources of known epitopes. Each epitope or set of epitopes was inserted into random amino acid sequence to create hypothetical proteins used as queries to an allergen database. Alignments with allergens were noted for the ability to match the epitope's source allergen as well as any cross-reactive or other homologous allergens. A FASTA expectation value range (1 × 10

Indexed as

AllergensAntigens, PlantComputational BiologyCross ReactionsEpitopesGlycoproteinsHumansImmunoglobulin EMembrane ProteinsPlant ProteinsSequence AlignmentAllergensAntigens, PlantAra h 1 protein, Arachis hypogaeaBet v 1 allergen, BetulaEpitopesGlycoproteinsImmunoglobulin EMembrane ProteinsPen a 1 allergen, Penaeus aztecusPlant ProteinsAllergenBioinformaticsCross-reactivityEpitopeFASTAHomology

Identifiers

PMID28191711
PMCPMC5573986
OpenAlexW2588605929

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.