Disease gene identification by using graph kernels and Markov random fields.
about
A fast and high performance multiple data integration algorithm for identifying human disease genes.A review on machine learning principles for multi-view biological data integration.Deciphering the Potential Pharmaceutical Mechanism of Chinese Traditional Medicine (Gui-Zhi-Shao-Yao-Zhi-Mu) on Rheumatoid ArthritisScuba: scalable kernel-based gene prioritization.Systems biology and metagenomics: a showcase of Chinese bioinformatics researchers and their work.Link Enrichment for Diffusion-Based Graph Node Kernels
P2860
Disease gene identification by using graph kernels and Markov random fields.
description
2014 nî lūn-bûn
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2014年の論文
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2014年学术文章
@wuu
2014年学术文章
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2014年学术文章
@zh-cn
2014年学术文章
@zh-hans
2014年学术文章
@zh-my
2014年学术文章
@zh-sg
2014年學術文章
@yue
2014年學術文章
@zh-hant
name
Disease gene identification by using graph kernels and Markov random fields.
@en
Disease gene identification by using graph kernels and Markov random fields.
@nl
type
label
Disease gene identification by using graph kernels and Markov random fields.
@en
Disease gene identification by using graph kernels and Markov random fields.
@nl
prefLabel
Disease gene identification by using graph kernels and Markov random fields.
@en
Disease gene identification by using graph kernels and Markov random fields.
@nl
P2093
P2860
P1476
Disease gene identification by using graph kernels and Markov random fields.
@en
P2093
BoLin Chen
Fang-Xiang Wu
JianXin Wang
P2860
P2888
P304
P356
10.1007/S11427-014-4745-8
P577
2014-10-17T00:00:00Z