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Projection-Based Neighborhood Non-Negative Matrix Factorization for lncRNA-Protein Interaction Prediction

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成果类型:
期刊论文
作者:
Ma, Yingjun;He, Tingting(何婷婷);Jiang, Xingpeng*蒋兴鹏
通讯作者:
Jiang, Xingpeng(蒋兴鹏
作者机构:
[Ma, Yingjun] Cent China Normal Univ, Sch Math & Stat, Wuhan, Hubei, Peoples R China.
[Jiang, Xingpeng; He, Tingting; Ma, Yingjun] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Hubei, Peoples R China.
[Jiang, Xingpeng; He, Tingting] Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.
通讯机构:
[Jiang, Xingpeng] C
Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Hubei, Peoples R China.
Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.
语种:
英文
关键词:
feature projection;graph non-negative matrix factorization;kernel neighborhood similarity;lncRNA-protein interaction;neighborhood completion
期刊:
Frontiers in Genetics
ISSN:
1664-8021
年:
2019
卷:
10
页码:
490530
基金类别:
This research is supported by National Key Research and Development Program of China (2017YFC0909502) and the National Natural Science Foundation of China (61532008 and 61872157).
机构署名:
本校为第一且通讯机构
院系归属:
数学与统计学学院
计算机学院
摘要:
Many long ncRNAs (lncRNA) make their effort by interacting with the corresponding RNA-binding proteins, and identifying the interactions between lncRNAs and proteins is important to understand the functions of lncRNA. Compared with the time-consuming and laborious experimental methods, more and more computational models are proposed to predict lncRNA-protein interactions. However, few models can effectively utilize the biological network topology of lncRNA (protein) and combine its sequence structure features, and most models cannot effectively predict new proteins (lncRNA) that do not interac...

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