Results 71 to 80 of about 1,535 (215)

Investigating microstructural variation in the human hippocampus using non-negative matrix factorization

NeuroImage, 2020
In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to ...
Raihaan Patel, Christopher J. Steele, Anthony G.X. Chen, Sejal Patel, Gabriel A. Devenyi, Jürgen Germann, Christine L. Tardif, M. Mallar Chakravarty   +7 more
doaj   +1 more source

Ordinal Non-negative Matrix Factorization for Recommendation

CoRR, 2020
Accepted for publication at ICML ...
Gouvert, Olivier, Oberlin, Thomas, Févotte, Cédric   +2 more
openaire   +5 more sources

USP29‐regulated noncanonical stabilization of the hypoxia‐inducible factor‐α in aggressive prostate cancer

Molecular Oncology, EarlyView.
We identify USP29 as the only DUB mirroring CA9 expression, a marker of hypoxia and HIF pathway activation associated with PCA aggressiveness. USP29 stabilizes HIF‐1α and HIF‐2α via a noncanonical mechanism that is independent of PHD/pVHL activity yet relies on proteasomal regulation, establishing USP29 as a previously unrecognized regulator of hypoxic
Amelie S Schober, Leire Moreno‐Cugnon, Laura Martínez‐Pérez, Amaia Ercilla, Amaia Zabala‐Letona, Adrián Vicente‐Barrueco, Maider Fagoaga‐Eugui, Saioa Garcia‐Longarte, Blanca Calle‐Ciborro, Encarnación Pérez‐Andrés, Onintza Carlevaris, Sara Pozo, Isabel Mendizabal, Ugo Mayor, Arkaitz Carracedo, Violaine Sée, Edurne Berra   +16 more
wiley   +1 more source

Locally Constrained Non-Negative Matrix Factorization for Data Clustering

IEEE Access
Semi-supervised non-negative matrix factorization (NMF) has been widely used for clustering high-dimensional data, because a small amount of label information can effectively improve clustering performance. Nevertheless, most existing semi-supervised NMF
Xuzhu Shen, Jie Li
doaj   +1 more source

Blind source separation with optimal transport non-negative matrix factorization

EURASIP Journal on Advances in Signal Processing, 2018
Optimal transport as a loss for machine learning optimization problems has recently gained a lot of attention. Building upon recent advances in computational optimal transport, we develop an optimal transport non-negative matrix factorization (NMF ...
Antoine Rolet, Vivien Seguy, Mathieu Blondel, Hiroshi Sawada   +3 more
doaj   +1 more source

MITF maintains genome stability in nonmelanocyte lineages

Molecular Oncology, EarlyView.
MITF is essential for melanocyte survival and acts as an oncogene in 10%–20% of melanomas. We show that MITF depletion causes genome instability in nonmelanocytic cells, leading to LATS2‐mediated P53 activation, cell cycle arrest, and apoptosis. This study highlights the role of MITF as a genome maintenance factor beyond the melanocyte lineage. Created
Drifa H. Gudmundsdottir, Adrián López García de Lomana, Thejus B. Venkatesh, Kritika Kirty, Snaevar Sigurdsson, Linda Vidarsdottir, Ramile Dilshat, Erla Sveinbjornsdottir, Snaedis Ragnarsdottir, Daniel H Magnusson, Maria R. Bustos, Eirikur Steingrimsson, Thorkell Gudjonsson, Stefan Sigurdsson   +13 more
wiley   +1 more source

Robust Semi-Supervised Non-Negative Matrix Factorization With Structured Normalization

IEEE Access, 2019
Non-negative matrix factorization (NMF) approximates a non-negative data matrix with the product of two low-rank non-negative matrices by minimizing the cost of such approximation.
Liujing Wang, Naiyang Guan, Dianxi Shi, Zunlin Fan, Longfei Su   +4 more
doaj   +1 more source

Non‐negative Matrix Factorization

, 2023
International audience ; Solving a source separation problem when the data are explained by a linear mixing of non-negative sources with non-negative mixing coefficients reduces to performing a non-negative factorization (NMF) of the data matrix. This chapter addresses the concept of NMF, discusses some of its geometrical aspects, presents the model ...
Brie, David, Gillis, Nicolas, Moussaoui, Saïd   +2 more
openaire   +1 more source

Oncogenic DMTF1β promotes cancer cell motility by regulating autophagy through ULK1 stabilization

Molecular Oncology, EarlyView.
In the current study, we demonstrate that the oncogene DMTF1β regulates ULK1 stability by reducing its proteasomal degradation in cancer cells. This stabilization enables ULK1 to induce autophagy, which in turn facilitates cancer cell migration. Consequently, reduced DMTF1β levels lead to decreased autophagy and impaired cancer cell migration.
Jun Xu, Nicolas J. Niklaus, Anna M. Schläfli, Igor Tokarchuk, Magali Humbert, Federico La Manna, Bich Vu, David Maul, Ramin Radpour, Marianna Kruithof‐de Julio, Inti Zlobec, Jörn Dengjel, Bruce E. Torbett, Mario P. Tschan   +13 more
wiley   +1 more source

In-memory analog computing for non-negative matrix factorization

Nature Communications
Non-negative matrix factorization (NMF) is a powerful technique for extracting latent structures from high-dimensional data, with applications spanning recommender systems, bioinformatics, and image processing.
Shiqing Wang, Yubiao Luo, Pushen Zuo, Yongxiang Li, Lunshuai Pan, Daniele Ielmini, Zhong Sun   +6 more
doaj   +1 more source