Results 81 to 90 of about 1,628,183 (185)

On restricted nonnegative matrix factorization [PDF]

, 2016
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matrix M into a product of a nonnegative n × d matrix W and a nonnegative d × m matrix H. Restricted NMF requires in addition that the column spaces of M and W
Kiefer, Stefan, Chistikov, D, Shirmohammadi, M, Worrell, J, Marusic, Ines, Worrell, James, Kiefer, SM, Kiefer, S., Shirmohammadi, M., Marusic, I, Shirmohammadi, Mashsa, Marusic, I., Shirmohammadi, Mahsa, Worrell, J., Chistikov, D., Kiefer, S, Chistikov, Dmitry   +16 more
core   +2 more sources

Uncovering Immune Niches in Health and Disease Using Spatial Transcriptomics

European Journal of Immunology, Volume 56, Issue 4, April 2026.
Through the lens of spatial transcriptomics and associated tools, novel immune niche constituents can now be resolved. Drawing on gut and tumor contexts, we propose a framework to define immune niches and integrate clonal dynamics, aiming to advance niche‐directed therapies toward precise, context‐specific immune modulation.
Johan Thorsson, Yang Zhao, Eduardo J. Villablanca, Camilla Engblom   +3 more
wiley   +1 more source

Nonnegative factorization and the maximum edge biclique problem [PDF]

Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a nonnegative matrix with a product of two nonnegative factors, which allows compression and interpretation of nonnegative data. In this paper, we study the
GILLIS, Nicolas, GLINEUR, François
core  

High ALG1 Expression Is Correlated With Poor Prognosis and the Immune Microenvironment in Glioma

Journal of Cellular and Molecular Medicine, Volume 30, Issue 8, April 2026.
ABSTRACT Glioma is the most prevalent primary tumour in the central nervous system. This study investigates ALG1 expression in glioma and its clinical significance. Using the TCGA and CGGA databases, a bioinformatics analysis examines ALG1 expression, its prognostic value, and its link to the immune microenvironment. Clinical samples are analysed using
Shuxiang Li, Yang Xia, Qiang Liu, Xin Qian, Anhong Liu, Jia Wang, Xinyu Wang, Di Zuo, Jing Zhang, Jinhai Ma, Peng Gao   +10 more
wiley   +1 more source

Projective robust nonnegative factorization

, 2016
Nonnegative matrix factorization (NMF) has been successfully used in many fields as a low-dimensional representation method. Projective nonnegative matrix factorization (PNMF) is a variant of NMF that was proposed to learn a subspace for feature ...
You, Jane, Xu, Yong, Lu, Yuwu, Lai, Z, Xu, Y, You, J, Lu, Y, Li, X, Li, Xuelong, Lai, Zhihui, Yuan, Chun, Yuan, C   +11 more
core   +1 more source

Regularized nonnegative matrix factorization: Geometrical interpretation and application to spectral unmixing

International Journal of Applied Mathematics and Computer Science, 2014
Nonnegative Matrix Factorization (NMF) is an important tool in data spectral analysis. However, when a mixing matrix or sources are not sufficiently sparse, NMF of an observation matrix is not unique.
Zdunek Rafał
doaj   +1 more source

Proteogenomic Characterization Reveals Subtype‐Specific Therapeutic Potential for HER2‐Low Breast Cancer

Advanced Science, Volume 13, Issue 12, 27 February 2026.
Multiomic profiling of HER2‐low breast cancer identifies three proteomic subtypes with distinct therapeutic strategies: endocrine, antiangiogenic, and anti‐HER2 therapies. Genomic and lactate modification landscapes are detailed, providing insights for precise management.
Shouping Xu, Keda Yu, Lei Liu, Qin Wang, Xiaohui Wu, Yihai Chen, Guozheng Li, Xin Zhang, Bo Wei, Zitong Fu, Abiyasi Nanding, Zuxianglan Zhao, Lingbing Yang, Xingda Zhang, Jianyu Wang, Wantong Sun, Yi Hao, Zhongyi Cheng, Xiaojiang Cui, Hao Wu, Da Pang   +20 more
wiley   +1 more source

Similarity Learning-Induced Symmetric Nonnegative Matrix Factorization for Image Clustering

IEEE Access, 2019
As a typical variation of nonnegative matrix factorization (NMF), symmetric NMF (SNMF) is capable of exploiting information of the cluster embedded in the matrix of similarity.
Wei Yan, Bob Zhang, Zuyuan Yang, Shengli Xie   +3 more
doaj   +1 more source

Nonnegative matrix factorization requires irrationality [PDF]

, 2017
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matrix M into a product of a nonnegative n × d matrix W and a nonnegative d × m matrix H. A longstanding open question, posed by Cohen and Rothblum in 1993, is
Kiefer, Stefan, Chistikov, D, James Worrell, Shirmohammadi, M, Worrell, J, Worrell, James, Marusic, I, Ines Marušić, Shirmohammadi, Mahsa, Dmitry Chistikov, Marušić, Ines, Mahsa Shirmohammadi, Kiefer, S, Stefan Kiefer, Chistikov, Dmitry   +14 more
core   +1 more source

Underwater acoustic target signal enhancement algorithm optimized by feature preservation and noise update [PDF]

Zhihui kongzhi yu fangzhen
The enhancement effect of the classic Nonnegative Matrix Factorization (NMF) applied to underwater acoustic target signal is unsatisfactory for the feature overlap of underwater acoustic target signal and the variability of ocean underwater acoustic ...
XIAO Haixia, CUI Shuangyue, LI Dawei, SUN Mingming, LIU Xianzhong, YANG Zhenxin
doaj   +1 more source