CLSTM Network.

<div><p>Background</p><p>Genome sequencing has enabled us to find functional peptides encoded by short open read frames (sORFs) in long non-coding RNAs (lncRNAs). sORFs-encoded peptides (SEPs) regulate gene expression, signaling, and so on and have significant roles, unlike c...

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Bibliographic Details
Main Author:	Hongqi Feng (14604437) (author)
Other Authors:	Qi Nie (5958599) (author), Sen Yang (88300) (author)
Published:	2025
Subjects:	Genetics Infectious Diseases Biological Sciences not elsewhere classified Information Systems not elsewhere classified regulate gene expression matthew correlation coefficient experimentally validated dataset ensemble learning strategy enhancing rich sequence various computational methods training characterization information mining feature information unlike common peptides logistic regression model throughput computational method curated traditional encoding sorfpp uses catboost identify seps based 2 %- 24 contributive traditional features traditional encoding computational method contributive features driven information encoded peptides attention model xlink "> two models sparsity problem sorfpp outperforms significant roles robust predictions predict seps multiple perspectives long non lncrnas ). including qsorder fused framework enabled us effective models coding rnas art models 5000 /</ 2 pre
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CLSTM Network.

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