Results 41 to 50 of about 20,683 (150)

LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates-1

, 2011
Copyright information:Taken from "LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates"BMC Bioinformatics 2006;7():175-175.Published online 28 Mar 2006PMCID:PMC1450309.Copyright © 2006 Wang et al; licensee BioMed
Andrew V Kossenkov (73124), Michael F Ochs (73125), Guoli Wang (59357)   +2 more
core   +1 more source

Joint Linear Regression and Nonnegative Matrix Factorization Based on Self-Organized Graph for Image Clustering and Classification

IEEE Access, 2018
Nonnegative matrix factorization (NMF) technique has been developed successfully to represent the intuitively meaningful feature of data. A suitable representation can faithfully preserve the intrinsic structure of data.
Wenjie Zhu, Yunhui Yan
doaj   +1 more source

Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization [PDF]

PeerJ, 2017
Single-cell RNA-Sequencing (scRNA-Seq) is a fast-evolving technology that enables the understanding of biological processes at an unprecedentedly high resolution.
Xun Zhu, Travers Ching, Xinghua Pan, Sherman M. Weissman, Lana Garmire   +4 more
doaj   +2 more sources

Features of the organization of space-planning solutions for nuclear medicine facilities [PDF]

BIO Web of Conferences
The purpose of this article is to determine the typology of the main functional zones for nuclear medicine facilities (NMF) and the formation of principles that affect the architecture of these typological zones.
Balakina Alevtina, Lempl Jury
doaj   +1 more source

ENDMEMBER EXTRACTION OF HIGHLY MIXED DATA USING L₁ SPARSITY-CONSTRAINED MULTILAYER NONNEGATIVE MATRIX FACTORIZATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
Due to the limited spatial resolution of remote hyperspectral sensors, pixels are usually highly mixed in the hyperspectral images. Endmember extraction refers to the process identifying the pure endmember signatures from the mixture, which is an ...
H. Fang, A. H. Li, H. X. Xu, T. Wang, K. Jiang, Y. Z. Su, H. W. Chang   +6 more
doaj   +1 more source

Application of spatially related MRF model in NMF hyperspectral unmixing

MATEC Web of Conferences, 2018
Aiming at Non-negative Matrix Factorization (NMF)’s problem of initialization and "local minima" in hyperspectral unmixing, a NMF linear unmixing algorithm with spatial correlation constrains (SCNMF) based on Markov Random Field (MRF) was proposed ...
Yuan Bo
doaj   +1 more source

LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates-0

, 2011
Copyright information:Taken from "LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates"BMC Bioinformatics 2006;7():175-175.Published online 28 Mar 2006PMCID:PMC1450309.Copyright © 2006 Wang et al; licensee BioMed
Andrew V Kossenkov (73124), Michael F Ochs (73125), Guoli Wang (59357)   +2 more
core   +1 more source

Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote homolog detection

BMC Bioinformatics, 2008
Background Nonnegative matrix factorization (NMF) is a feature extraction method that has the property of intuitive part-based representation of the original features.
Lee Soo-Young, Lee Jaehyung, Jung Inkyung, Kim Dongsup   +3 more
doaj   +1 more source

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

eLife, 2022
Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor ...
Gabriel Renaud, Maibritt Nørgaard, Johan Lindberg, Henrik Grönberg, Bram De Laere, Jørgen Bjerggaard Jensen, Michael Borre, Claus Lindbjerg Andersen, Karina Dalsgaard Sørensen, Lasse Maretty, Søren Besenbacher   +10 more
doaj   +1 more source

Graphical illustration of PCA(A), NMF(B), and sparse NMF(C).

, 2023
The matrix factorizations are reduced from three to two dimensions. PCA covers the solutions with a hyperplane, NMF constraints them between two vectors, and sparse NMF forces the solutions to be in the vicinity to the vectors.
János Abonyi (10106040), Ádám Ipkovich (15285785), Gyula Dörgő (13919393), Károly Héberger (390762)   +3 more
core   +1 more source