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pLMSNOSite: an ensemble-based approach for predicting prote..:
Pawel Pratyush
;
Suresh Pokharel
;
Hiroto Saigo
.
https://doi.org/10.1186/s12859-023-05164-9. , 2023
Link:
https://doi.org/10.1186/s12859-023-05164-9
RT Journal T1
pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:24358939c36148d098270c815601afab&Exemplar=1&LAN=DE A1 Pawel Pratyush A1 Suresh Pokharel A1 Hiroto Saigo A1 Dukka B. KC PB BMC YR 2023 K1 S-nitrosylation K1 Deep learning K1 Convolutional neural network K1 Post-translational modification K1 Word embedding K1 Protein language model K1 Computer applications to medicine. Medical informatics K1 R858-859.7 K1 Biology (General) K1 QH301-705.5 JF https://doi.org/10.1186/s12859-023-05164-9 LK http://dx.doi.org/https://doi.org/10.1186/s12859-023-05164-9 DO https://doi.org/10.1186/s12859-023-05164-9 SF ELIB - SuUB Bremen
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