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Automated benchmarking of peptide-MHC class I binding predictions

Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility complex (MHC) class I molecules have been developed over the last decades. However, the multitude of available prediction tools makes it non-trivial for the end-user to select which tool to use for a given...

詳細記述

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書誌詳細
出版年:Bioinformatics
主要な著者: Trolle, Thomas, Metushi, Imir G., Greenbaum, Jason A., Kim, Yohan, Sidney, John, Lund, Ole, Sette, Alessandro, Peters, Bjoern, Nielsen, Morten
フォーマット: Artigo
言語:Inglês
出版事項: Oxford University Press 2015
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC4481849/
https://ncbi.nlm.nih.gov/pubmed/25717196
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btv123
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