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Function prediction of cancer-related LncRNAs using heterogeneous information network model
被引:1
作者:
Kumar, P. V. Sunil
[1
]
Manju, M.
[2
]
Gopakumar, G.
[1
]
机构:
[1] Natl Inst Technol Calicut, Dept Comp Sci & Engn, NIT Campus PO, Kozhikkode 673601, Kerala, India
[2] KSM Devaswom Board Coll Sasthamkotta, Dept Zool, Kollam 690521, Kerala, India
关键词:
LncRNA;
cancer;
heterogeneous information network;
meta-path;
classification;
support vector machine;
machine learning;
oncogenic;
tumour suppressor;
LONG NONCODING RNA;
CELL-PROLIFERATION;
TUMOR-SUPPRESSOR;
DOWN-REGULATION;
POOR-PROGNOSIS;
GASTRIC-CANCER;
PROGRESSION;
EXPRESSION;
DATABASE;
CERNA;
D O I:
10.1504/IJDMB.2018.098940
中图分类号:
Q [生物科学];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
The aberrant expression of lncRNAs is proven to be one of the prime reasons for cancer progression. Recent studies recommend lncRNAs as potential therapeutic target in cancer. The overexpression of oncogenic lncRNAs causes tumour progression, whereas that of tumour suppressor lncRNAs leads to apoptosis. In this paper, a heterogeneous information network-based Support Vector Machine classifier that can predict lncRNAs into oncogenic or tumour suppressor is proposed. Interactions of lncRNAs with other lncRNAs and proteins along with protein-protein interactions are used to build the network. The model predicted lncRNAs into oncogenic or tumour suppressor with an accuracy of 0.83 and produced an accuracy of 0.80 during an independent validation. A comparison with recently reported studies shows that prediction results fall in line with them.
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页码:315 / 338
页数:24
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