Optimizing lipocalin sequence classification with ensemble deep learning models
Optimizing lipocalin sequence classification with ensemble deep learning models
About this item
Full title
Author / Creator
Zhang, Yonglin , Yu, Lezheng , Xue, Li , Liu, Fengjuan , Jing, Runyu and Luo, Jiesi
Publisher
United States: Public Library of Science
Journal title
Language
English
Formats
Publication information
Publisher
United States: Public Library of Science
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Scope and Contents
Contents
Deep learning (DL) has become a powerful tool for the recognition and classification of biological sequences. However, conventional single-architecture models often struggle with suboptimal predictive performance and high computational costs. To address these challenges, we present EnsembleDL-Lipo, an innovative ensemble deep learning framework tha...
Alternative Titles
Full title
Optimizing lipocalin sequence classification with ensemble deep learning models
Authors, Artists and Contributors
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Record Identifier
TN_cdi_plos_journals_3191113968
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_3191113968
Other Identifiers
ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0319329
