Results 51 to 60 of about 20,683 (150)

Stratified-NMF for Heterogeneous Data [PDF]

, 2023
Non-negative matrix factorization (NMF) is an important technique for obtaining low dimensional representations of datasets. However, classical NMF does not take into account data that is collected at different times or in different locations, which may ...
Needell, Deanna, Chapman, James, Yaniv, Yotam   +2 more
core   +1 more source

A new gene-scoring method for uncovering novel glaucoma-related genes using non-negative matrix factorization based on RNA-seq data

Frontiers in Genetics, 2023
Early diagnosis and treatment of glaucoma are challenging. The discovery of glaucoma biomarkers based on gene expression data could potentially provide new insights for early diagnosis, monitoring, and treatment options of glaucoma.
Xiaoqin Huang, Akhilesh K. Bajpai, Jian Sun, Fuyi Xu, Fuyi Xu, Lu Lu, Lu Lu, Siamak Yousefi, Siamak Yousefi   +8 more
doaj   +1 more source

A flexible R package for nonnegative matrix factorization

BMC Bioinformatics, 2010
Background Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have
Seoighe Cathal, Gaujoux Renaud
doaj   +1 more source

Accurate image derived input function in [18F]SynVesT-1 mouse studies using isoflurane and ketamine/xylazine anesthesia

EJNMMI Physics, 2023
Background Kinetic modeling in positron emission tomography (PET) requires measurement of the tracer plasma activity in the absence of a suitable reference region.
Alan Miranda, Daniele Bertoglio, Steven Staelens, Jeroen Verhaeghe   +3 more
doaj   +1 more source

nmf

, 2019
Inputs and results of non-negative matrix factorization (NMF) analyses for various subsets of cells. We make use of NMF results throughout the analyses (see analysis files in archives Hydra_Seurat_NMF_regulators_analyses and Hydra_URD_analysis).
Cazet, Jack F.
core   +1 more source

A framework for regularized non-negative matrix factorization, with application to the analysis of gene expression data.

PLoS ONE, 2012
Non-negative matrix factorization (NMF) condenses high-dimensional data into lower-dimensional models subject to the requirement that data can only be added, never subtracted.
Leo Taslaman, Björn Nilsson
doaj   +1 more source

Analyze the robustness of three NMF algorithms (Robust NMF with L1 norm, L2-1 norm NMF, L2 NMF)

, 2023
Non-negative matrix factorization (NMF) and its variants have been widely employed in clustering and classification tasks (Long, & Jian , 2021). However, noises can seriously affect the results of our experiments.
Xu, Yixuan, Zeng, Cheng, Tian, Jiaqi
core  

MEASUREMENT ERROR DECONVOLUTION METHODS AND RANK SELECTION FOR NON-NEGATIVE MATRIX FACTORIZATION WITH APPLICATIONS IN MICROBIOME DATA

, 2022
Learning the structure of microbial communities is critical in understanding the different community structures and functions of microbes in distinct individuals.
Cai, Yun
core  

NMF on positron emission tomography [PDF]

, 2007
In positron emission tomography, kinetic modelling of brain tracer uptake, metabolism or binding requires knowledge of the cerebral input function. Traditionally, this is achieved with arterial blood sampling in the arm or as shown in (Liptrot, M, et al.,
Bödvarsson, Bjarni, Bjarni Bodvarsson, Gitte Knudsen, Knudsen, Gitte, Lars Kai Hansen, Hansen, Lars Kai, Claus Svarer, Svarer, Claus   +7 more
core   +1 more source

Nonnegative matrix factorization with Wasserstein metric-based regularization for enhanced text embedding.

PLoS ONE
Text embedding plays a crucial role in natural language processing (NLP). Among various approaches, nonnegative matrix factorization (NMF) is an effective method for this purpose.
Mingming Li, Xingjie Wang, Chunhua Li, Anping Zeng   +3 more
doaj   +1 more source