ResLysEmbed: a ResNet-based framework for succinylated lysine residue prediction using sequence and language model embeddings

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Journal
Bioinformatics Advances
Published
2024-12-26
DOI
https://doi.org/10.1093/bioadv/vbaf198
Primary Topic
Machine Learning in Bioinformatics
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article
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article

ResLysEmbed: a ResNet-based framework for succinylated lysine residue prediction using sequence and language model embeddings

Souvik Ghosh, M. Saifur Rahman, Md Muhaiminul Islam Nafi
Bioinformatics Advances
Machine Learning in Bioinformatics
article

ResLysEmbed: a ResNet-based framework for succinylated lysine residue prediction using sequence and language model embeddings

Souvik Ghosh, M. Saifur Rahman, Md Muhaiminul Islam Nafi
article en

Abstract

No abstract available for this paper.
Bioinformatics AdvancesVol. 5(1)
Bangladesh University of Engineering and Technology (BD), BRAC University (BD), United International University (BD)
Openalex Percentile: Top 77%
Machine Learning in Bioinformatics
DOIOpen Access PDFOpenAlex
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ResLysEmbed: a ResNet-based framework for succinylated lysine residue prediction using sequence and language model embeddings — Souvik Ghosh, M. Saifur Rahman, et al. · Bioinformatics Advances (2024) | TGRS Research Map | TGRS