A Hybrid Prediction Method for Plant lncRNA-Protein Interaction

Long non-protein-coding RNAs (lncRNAs) identification and analysis are pervasive in transcriptome studies due to their roles in biological processes. In particular, lncRNA-protein interaction has plausible relevance to gene expression regulation and in cellular processes such as pathogen resistance...

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Veröffentlicht in:	Cells (Basel, Switzerland) Jg. 8; H. 6; S. 521
Hauptverfasser:	Wekesa, Jael Sanyanda, Luan, Yushi, Chen, Ming, Meng, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 30.05.2019 MDPI
Schlagworte:	Algorithms Arabidopsis - genetics Arabidopsis thaliana Artificial intelligence autoencoder Bioinformatics Compression Computational Biology - methods Deep learning Deoxyribonucleic acid DNA Gene expression Gene regulation hybrid International conferences Learning algorithms light gradient boosting machine lncRNA-protein interaction Localization Machine learning Neural networks plant Plant diseases Plant Proteins - metabolism Prediction models Protein Binding random forest Research methodology RNA, Long Noncoding - genetics RNA, Long Noncoding - metabolism RNA-protein interactions ROC Curve Zea mays Zea mays - genetics United States > US China autoencoder hybrid random forest light gradient boosting machine lncRNA-protein interaction plant
ISSN:	2073-4409, 2073-4409
Online-Zugang:	Volltext
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