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Prediction of the disulfide-bonding state of cysteines in proteins at 88% accuracy

The task of predicting the cysteine-bonding state in proteins starting from the residue chain is addressed by implementing a new hybrid system that combines a neural network and a hidden Markov model (hidden neural network). Training is performed using 4136 cysteine-containing segments extracted fro...

詳細記述

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書誌詳細
主要な著者: Martelli, Pier Luigi, Fariselli, Piero, Malaguti, Luca, Casadio, Rita
フォーマット: Artigo
言語:Inglês
出版事項: Cold Spring Harbor Laboratory Press 2002
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC2373728/
https://ncbi.nlm.nih.gov/pubmed/12381855
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