Deep forest ensemble learning for classification of alignments of non-coding RNA sequences based on multi-view structure representations

Abstract Non-coding RNAs (ncRNAs) play crucial roles in multiple biological processes. However, only a few ncRNAs’ functions have been well studied. Given the significance of ncRNAs classification for understanding ncRNAs’ functions, more and more computational methods have been introduced to improv...

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Veröffentlicht in:	Briefings in bioinformatics Jg. 22; H. 4
Hauptverfasser:	Li, Ying, Zhang, Qi, Liu, Zhaoqian, Wang, Cankun, Han, Siyu, Ma, Qin, Du, Wei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Oxford University Press 01.07.2021 Oxford Publishing Limited (England)
Schlagworte:	Algorithms Alignment Artificial neural networks Biological activity Classification Clustering Computer applications Ensemble learning Gene sequencing Machine learning Neural networks Non-coding RNA Phylogenetics Phylogeny Representations Source code GcForest ncRNAs clustering deep fusion framework multi-view structure feature representation pairwise ncRNAs classification
ISSN:	1467-5463, 1477-4054, 1477-4054
Online-Zugang:	Volltext
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