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Predicting virus-host association by Kernelized logistic matrix factorization and similarity network fusion

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成果类型:
期刊论文、会议论文
作者:
Liu, Dan;Ma, Yingjun;Jiang, Xingpeng*蒋兴鹏);He, Tingting*何婷婷
通讯作者:
Jiang, Xingpeng(蒋兴鹏);He, Tingting(何婷婷
作者机构:
[Jiang, Xingpeng; He, Tingting; Ma, Yingjun; Liu, Dan] Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.
[He, Tingting; Ma, Yingjun; Liu, Dan] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Hubei, Peoples R China.
通讯机构:
[Jiang, XP; He, TT] C
Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.
语种:
英文
关键词:
Virus-host association;Logistic matrix factorization;Similarity network fusion;Oligonucleotide frequency;Gaussian interaction profile
期刊:
BMC Bioinformatics
ISSN:
1471-2105
年:
2019
卷:
20
期:
Suppl 16
页码:
1-10
会议名称:
IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - Bioinformatics and Systems Biology
会议时间:
DEC 03-06, 2018
会议地点:
Madrid, SPAIN
会议主办单位:
[Liu, Dan;Ma, Yingjun;Jiang, Xingpeng;He, Tingting] Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.^[Liu, Dan;Ma, Yingjun;Jiang, Xingpeng;He, Tingting] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Hubei, Peoples R China.
会议赞助商:
IEEE
出版地:
CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
出版者:
BMC
基金类别:
The research was supported by the National Key Research and Development Program of China (2017YFC0909502), the National Natural Science Foundation of China (61532008, 61872157). Specifically, the publication costs are funded by the National Key Research and Development Program of China (2017YFC0909502).
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
Background: Viruses are closely related to bacteria and human diseases. It is of great significance to predict associations between viruses and hosts for understanding the dynamics and complex functional networks in microbial community. With the rapid development of the metagenomics sequencing, some methods based on sequence similarity and genomic homology have been used to predict associations between viruses and hosts. However, the known virus-host association network was ignored in these methods. Results: We proposed a kernelized logistic ma...

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