Results 71 to 80 of about 142,276 (359)
This study investigated how PYCR1 inhibition in bone marrow stromal cells (BMSCs) indirectly affects multiple myeloma (MM) cell metabolism and viability. Culturing MM cells in conditioned medium from PYCR1‐silenced BMSCs impaired oxidative phosphorylation and increased sensitivity to bortezomib.
Inge Oudaert +13 more
wiley +1 more source
Semantic Non-Negative Matrix Factorization for Term Extraction
This study introduces an unsupervised term extraction approach that combines non-negative matrix factorization (NMF) with word embeddings. Inspired by a pioneering semantic NMF method that employs regularization to jointly optimize document–word and word–
Aliya Nugumanova +4 more
doaj +1 more source
Non Negative Matrix Factorization Clustering Capabilities; Application on Multivariate Image Segmentation [PDF]
The clustering capabilities of the Non Negative MatrixFactorization algorithm is studied. The basis images are consideredlike the data membership degree to a particular class.A hard clustering algorithm is easily derived based on theseimages.
Cosmin Lazar +3 more
doaj
Infinite Non-Negative Matrix Factorization
Publication in the conference proceedings of EUSIPCO, Aalborg, Denmark ...
Mørup, Morten, Schmidt, Mikkel
openaire +1 more source
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker +16 more
wiley +1 more source
Document Clustering Based On Max-Correntropy Non-Negative Matrix Factorization [PDF]
Nonnegative matrix factorization (NMF) has been successfully applied to many areas for classification and clustering. Commonly-used NMF algorithms mainly target on minimizing the $l_2$ distance or Kullback-Leibler (KL) divergence, which may not be ...
Li, Le +4 more
core
Multifrontal Non-negative Matrix Factorization
Non-negative matrix factorization (Nmf) is an important tool in high-performance large scale data analytics with applications ranging from community detection, recommender system, feature detection and linear and non-linear unmixing. While traditional Nmf works well when the data set is relatively dense, however, it may not extract sufficient structure
Piyush Sao, Ramakrishnan Kannan
openaire +2 more sources
A mouse model for vascular normalization and a human breast cancer cohort were studied to understand the relationship between vascular leakage and tumor immune suppression. For this, endothelial and immune cell RNAseq, staining for vascular function, and immune cell profiling were employed.
Liqun He +8 more
wiley +1 more source
KOMPRESI DAN PENGENALAN CITRA WAJAH DENGAN PENDEKATAN NON-NEGATIVE MATRIX FACTORIZATION [PDF]
KOMPRESI DAN PENGENALAN CITRA WAJAH DENGAN PENDEKATAN NON-NEGATIVE MATRIX FACTORIZATION - Face recognition, kompresi, Non-negative Matrix Factorization, Principal Component Analysis, Eigenface, Computer ...
BENNY KURNIAWAN USODO, FICTOR +2 more
core
Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz +15 more
wiley +1 more source

