Results 91 to 100 of about 142,276 (359)
Strength through diversity: how cancers thrive when clones cooperate
Intratumor heterogeneity can offer direct benefits to the tumor through cooperation between different clones. In this review, Kuiken et al. discuss existing evidence for clonal cooperativity to identify overarching principles, and highlight how novel technological developments could address remaining open questions.
Marije C. Kuiken +3 more
wiley +1 more source
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization [PDF]
The separability assumption (Donoho & Stodden, 2003; Arora et al., 2012) turns non-negative matrix factorization (NMF) into a tractable problem. Recently, a new class of provably-correct NMF algorithms have emerged under this assumption.
Kambadur, Prabhanjan +2 more
core
Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice +16 more
wiley +1 more source
Robust Hierarchical Learning for Non-Negative Matrix Factorization With Outliers
Desirable properties of extensions of non-negative matrix factorization (NMF) include robustness in the presence of noises and outliers, ease of implementation, the guarantee of convergence, operation in an automatic fashion that trades off the balance ...
Yinan Li +4 more
doaj +1 more source
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been applied in several applications, it does not always result in parts-based ...
Patrik O. Hoyer, Peter Dayan
core +1 more source
Enforced Sparse Non-negative Matrix Factorization [PDF]
Non-negative matrix factorization (NMF) is a dimensionality reduction algorithm for data that can be represented as an undirected bipartite graph. It has become a common method for generating topic models of text data because it is known to produce good results, despite its relative simplicity of implementation and ease of computation.
Brendan Gavin +2 more
openaire +1 more source
Potential therapeutic targeting of BKCa channels in glioblastoma treatment
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak +4 more
wiley +1 more source
Cell surface interactome analysis identifies TSPAN4 as a negative regulator of PD‐L1 in melanoma
Using cell surface proximity biotinylation, we identified tetraspanin TSPAN4 within the PD‐L1 interactome of melanoma cells. TSPAN4 negatively regulates PD‐L1 expression and lateral mobility by limiting its interaction with CMTM6 and promoting PD‐L1 degradation.
Guus A. Franken +7 more
wiley +1 more source
Robust Ensemble Manifold Projective Non-Negative Matrix Factorization for Image Representation
Projective non-negative matrix factorization (PNMF) as a variant of NMF has received considerable attention. However, the existing PNMF methods can be further improved from two aspects.
Peng Luo +7 more
doaj +1 more source
LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix +13 more
wiley +1 more source

