Home ›
Entities
› academia
› 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
Research article (BMC Bioinformatics, 2023) · cited 31× · AI/ML
pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model
Summary
pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model is a scholarly article[1].
Key Facts
pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model. Retrieved May 24, 2026, from https://4ort.xyz/entity/plmsnosite-an-ensemble-based-approach-for-predicting-protein-s-nitrosylation-sites-by-integrating-supervised-word-embedd
MLA“pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/plmsnosite-an-ensemble-based-approach-for-predicting-protein-s-nitrosylation-sites-by-integrating-supervised-word-embedd.
BibTeX@misc{4ortxyz_plmsnosite-an-ensemble-based-approach-for-predicting-protein-s-nitrosylation-sites-by-integrating-supervised-word-embedd_2026, author = {{4ort.xyz Knowledge Graph}}, 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}}, year = {2026}, url = {https://4ort.xyz/entity/plmsnosite-an-ensemble-based-approach-for-predicting-protein-s-nitrosylation-sites-by-integrating-supervised-word-embedd}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model — https://4ort.xyz/entity/plmsnosite-an-ensemble-based-approach-for-predicting-protein-s-nitrosylation-sites-by-integrating-supervised-word-embedd (retrieved 2026-05-24)
