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Title: pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model
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 biological processes including immune response, protein stability, transcription regulation, post translational regulation, DNA damage repair, redox regulation, and is an emerging paradigm of redox signaling for protection against oxidative stress. The development of robust computational tools to predict protein SNO sites would contribute to further interpretation of the pathological and physiological mechanisms of SNO.  more » « less
Award ID(s):
1901191
PAR ID:
10481200
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Springer Nature
Date Published:
Journal Name:
BMC bioinformatics
ISSN:
1471-2105
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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