Matrix decomposition Archives - Transactions on NanoBioscience (TNB)

August 17, 2017

Robust and Efficient Biomolecular Clustering of Tumor Based on p -Norm Singular Value Decomposition

Author(s)3: Xiang-Zhen Kong, Jin-Xing Liu, Chun-Hou Zheng, Mi-Xiao Hou, Juan Wang

Robust and Efficient Biomolecular Clustering of Tumor Based on p -Norm Singular Value Decomposition https://www.embs.org/tnb/wp-content/uploads/sites/16/2017/08/Liu.png 215 235 Transactions on NanoBioscience (TNB) Transactions on NanoBioscience (TNB) //www.embs.org/tnb/wp-content/uploads/sites/16/2022/06/ieee-tnb-logo2x.png August 17, 2017 March 4, 2022

High dimensionality has become a typical feature of biomolecular data. In this paper, a novel dimension reduction method named p-norm singular value decomposition (PSVD) is proposed to seek the low-rank…

November 3, 2016

Block-Constraint Robust Principal Component Analysis and its Application to Integrated Analysis of TCGA Data

Author(s)3: Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu, Jiguo Yu

Block-Constraint Robust Principal Component Analysis and its Application to Integrated Analysis of TCGA Data https://www.embs.org/tnb/wp-content/uploads/sites/16/2016/11/Liu.png 215 259 Transactions on NanoBioscience (TNB) Transactions on NanoBioscience (TNB) //www.embs.org/tnb/wp-content/uploads/sites/16/2022/06/ieee-tnb-logo2x.png November 3, 2016 March 4, 2022

The Cancer Genome Atlas (TCGA) dataset provides us more opportunities to systematically and comprehensively learn some biological mechanism of cancers formation, growth and metastasis. Since TCGA dataset includes heterogeneous data,…