Multi-view Subspace Clustering Analysis for Aggregating Multiple Heterogeneous Omics Data

Multi-view Subspace Clustering Analysis for Aggregating Multiple Heterogeneous Omics Data

Integration of distinct biological data types could provide a comprehensive view of biological processes or complex diseases. The combinations of molecules responsible for different phenotypes form multiple embedded (expression) subspaces, thus identifying the intrinsic data structure is challenging...

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Bibliographic Details
Main Authors: Qianqian Shi, Bing Hu, Tao Zeng, Chuanchao Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-08-01
Series:Frontiers in Genetics
Subjects:
multi-view subspace clustering analysis
data integration
heterogeneity
low-rank representation
graph diffusion
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2019.00744/full

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https://www.frontiersin.org/article/10.3389/fgene.2019.00744/full

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