Clustering of Cancer Attributed Networks via Integration of Graph Embedding and Matrix Factorization

Clustering of Cancer Attributed Networks via Integration of Graph Embedding and Matrix Factorization

Advances in bio-technologies enable the generation of genomic data from various platforms. The accumulated omic data provides an opportunity to exploit the underlying mechanisms of cancers, and imposes a great challenge on designing algorithms for the integration of heterogeneous genomic data. Clust...

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Bibliographic Details
Main Authors: Qiang Lin, Yong Lin, Qiang Yu, Xiaoke Ma
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Graph clustering
attributed networks
nonnegative matrix factorization
graph embedding
Online Access:https://ieeexplore.ieee.org/document/9244081/

Internet

https://ieeexplore.ieee.org/document/9244081/

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