Dual Graph-Laplacian PCA: A Closed-Form Solution for Bi-Clustering to Find “Checkerboard” Structures on Gene Expression Data

Dual Graph-Laplacian PCA: A Closed-Form Solution for Bi-Clustering to Find “Checkerboard” Structures on Gene Expression Data

In the context of cancer, internal “checkerboard” structures are normally found in the matrices of gene expression data, which correspond to genes that are significantly up- or down-regulated in patients with specific types of tumors. In this paper, we propose a novel method, c...

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Bibliographic Details
Main Authors: Jin-Xing Liu, Chun-Mei Feng, Xiang-Zhen Kong, Yong Xu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Bi-clustering
gene expression data
Laplacian embedding
principal component analysis
Online Access:https://ieeexplore.ieee.org/document/8836466/

Internet

https://ieeexplore.ieee.org/document/8836466/

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