A Hybrid Recurrent Neural Network/Dynamic Probabilistic Graphical Model Predictor of the Disulfide Bonding State of Cysteines from the Primary Structure of Proteins-Reference-Cited by-同舟云学术

A Hybrid Recurrent Neural Network/Dynamic Probabilistic Graphical Model Predictor of the Disulfide Bonding State of Cysteines from the Primary Structure of Proteins

Published:2016 Issue: Volume: Page:257-268
ISSN:0302-9743
Container-title:Artificial Neural Networks in Pattern Recognition
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Author:

Bongini Marco,Laveglia Vincenzo,Trentin Edmondo

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-46182-3_22

Reference19 articles.

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5. Ceroni, A., Passerini, A., Vullo, A., Frasconi, P.: DISULFIND: a disulfide bonding state and cysteine connectivity prediction server. Nucleic Acids Res. 34(Web-Server-Issue), 177–181 (2006)

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