About: Flexible machine learning prediction of antigen presentation for rare and common HLA-I alleles

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About: Flexible machine learning prediction of antigen presentation for rare and common HLA-I alleles Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Flexible machine learning prediction of antigen presentation for rare and common HLA-I alleles
Creator	Cocco, Simona Monasson, Rémi Mora, Thierry Walczak, Aleksandra Bravi, Barbara »more»
source	BioRxiv
abstract	The recent increase of immunopeptidomic data, obtained by mass spectrometry (MS) or binding assays, opens unprecedented possibilities for investigating endogenous antigen presentation by the highly polymorphic human leukocyte antigen class I (HLA-I) protein. We introduce a flexible and easily interpretable peptide presentation prediction method. We validate its performance as a predictor of cancer neoantigens and viral epitopes and use it to reconstruct peptide motifs presented on specific HLA-I molecules.
has issue date	2020-04-25(xsd:dateTime)
bibo:doi	10.1101/2020.04.25.061069
has license	biorxiv
sha1sum (hex)	fafa825456687b9338ad5569ad3e82ae45b363e4
schema:url	https://doi.org/10.1101/2020.04.25.061069
resource representing a document's title	Flexible machine learning prediction of antigen presentation for rare and common HLA-I alleles
schema:publication	bioRxiv
resource representing a document's body	covid:fafa825456687b9338ad5569ad3e82ae45b363e4#body_text
is schema:about of	named entity 'peptide' named entity 'HLA-I' named entity 'antigen presentation' named entity 'machine learning' covid:arg/fafa825456687b9338ad5569ad3e82ae45b363e4 »more»

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