Joint Lp-Norm and L(2,1)-Norm Constrained Graph Laplacian PCA for Robust Tumor Sample Clustering and Gene Network Module Discovery

The dimensionality reduction method accompanied by different norm constraints plays an important role in mining useful information from large-scale gene expression data. In this article, a novel method named Lp-norm and L(2,1)-norm constrained graph Laplacian principal component analysis (PL21GPCA)...

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Detalles Bibliográficos
Autores principales: Kong, Xiang-Zhen, Song, Yu, Liu, Jin-Xing, Zheng, Chun-Hou, Yuan, Sha-Sha, Wang, Juan, Dai, Ling-Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940841/
https://www.ncbi.nlm.nih.gov/pubmed/33708239
http://dx.doi.org/10.3389/fgene.2021.621317

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940841/
https://www.ncbi.nlm.nih.gov/pubmed/33708239
http://dx.doi.org/10.3389/fgene.2021.621317

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