pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model

pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model

Abstract Background Protein S-nitrosylation (SNO) plays a key role in transferring nitric oxide-mediated signals in both animals and plants and has emerged as an important mechanism for regulating protein functions and cell signaling of all main classes of protein. It is involved in several biologic...

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Bibliographic Details
Main Authors: Pawel Pratyush, Suresh Pokharel, Hiroto Saigo, Dukka B. KC
Format: Article
Language:English
Published: BMC 2023-02-01
Series:BMC Bioinformatics
Subjects:
S-nitrosylation
Deep learning
Convolutional neural network
Post-translational modification
Word embedding
Protein language model
Online Access:https://doi.org/10.1186/s12859-023-05164-9

Internet

https://doi.org/10.1186/s12859-023-05164-9

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