Graph embedding ensemble methods based on the heterogeneous network for lncRNA-miRNA interaction prediction
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Title
Graph embedding ensemble methods based on the heterogeneous network for lncRNA-miRNA interaction prediction
Authors
Keywords
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Journal
BMC GENOMICS
Volume 21, Issue S13, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-12-17
DOI
10.1186/s12864-020-07238-x
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- (2017) Yan-Bin Wang et al. Molecular BioSystems
- A Positive Feedback Loop of lncRNA- PVT1 and FOXM1 Facilitates Gastric Cancer Growth and Invasion
- (2016) Mi-die Xu et al. CLINICAL CANCER RESEARCH
- Predicting drug side effects by multi-label learning and ensemble learning
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- Drug–target interaction prediction: databases, web servers and computational models
- (2015) Xing Chen et al. BRIEFINGS IN BIOINFORMATICS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Noncoding RNA and its associated proteins as regulatory elements of the immune system
- (2014) Martin Turner et al. NATURE IMMUNOLOGY
- lncRNASNP: a database of SNPs in lncRNAs and their potential functions in human and mouse
- (2014) Jing Gong et al. NUCLEIC ACIDS RESEARCH
- Functional interactions among microRNAs and long noncoding RNAs
- (2014) Je-Hyun Yoon et al. SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
- The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer
- (2014) Dimple Chakravarty et al. Nature Communications
- Evf2 (Dlx6as) lncRNA regulates ultraconserved enhancer methylation and the differential transcriptional control of adjacent genes
- (2013) E. G. Berghoff et al. DEVELOPMENT
- Long non-coding RNAs: new players in cell differentiation and development
- (2013) Alessandro Fatica et al. NATURE REVIEWS GENETICS
- LncRNA loc285194 is a p53-regulated tumor suppressor
- (2013) Qian Liu et al. NUCLEIC ACIDS RESEARCH
- Computational Prediction of Conformational B-Cell Epitopes from Antigen Primary Structures by Ensemble Learning
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- MiR-106a inhibits glioma cell growth by targeting E2F1 independent of p53 status
- (2011) Guang Yang et al. JOURNAL OF MOLECULAR MEDICINE-JMM
- A Review of Ensemble Methods in Bioinformatics
- (2010) Pengyi Yang et al. Current Bioinformatics
- Detection of miR-106a in gastric carcinoma and its clinical significance
- (2008) Bingxiu Xiao et al. CLINICA CHIMICA ACTA
- An Analysis of Human MicroRNA and Disease Associations
- (2008) Ming Lu et al. PLoS One
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