Non-Negative Symmetric Low-Rank Representation Graph Regularized Method for Cancer Clustering Based on Score Function

Non-Negative Symmetric Low-Rank Representation Graph Regularized Method for Cancer Clustering Based on Score Function

As an important approach to cancer classification, cancer sample clustering is of particular importance for cancer research. For high dimensional gene expression data, examining approaches to selecting characteristic genes with high identification for cancer sample clustering is an important researc...

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Bibliographic Details
Main Authors: Conghai Lu, Juan Wang, Jinxing Liu, Chunhou Zheng, Xiangzhen Kong, Xiaofeng Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-01-01
Series:Frontiers in Genetics
Subjects:
cancer gene expression data
low-rank representation
feature selection
score function
clustering
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2019.01353/full

Internet

https://www.frontiersin.org/article/10.3389/fgene.2019.01353/full

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