Results 91 to 100 of about 232,386 (277)
A Topological Approach to Spectral Clustering
We propose two related unsupervised clustering algorithms which, for input, take data assumed to be sampled from a uniform distribution supported on a metric space $X$, and output a clustering of the data based on the selection of a topological model for
Rieser, Antonio
core
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
Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged as prevailing methods for efficiently recovering sparse and partially ...
Hunter, Blake, Strohmer, Thomas
core
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
Plecstatin inhibits hepatocellular carcinoma tumorigenesis and invasion through cytolinker plectin
The ruthenium‐based metallodrug plecstatin exerts its anticancer effect in hepatocellular carcinoma (HCC) primarily through selective targeting of plectin. By disrupting plectin‐mediated cytoskeletal organization, plecstatin inhibits anchorage‐dependent growth, cell polarization, and tumor cell dissemination.
Zuzana Outla +10 more
wiley +1 more source
Newtonian Spectral Clustering [PDF]
In this study we propose a systematic methodology for constructing a sparse affinity matrix to be used in an advantageous spectral clustering approach. Newton's equations of motion are employed to concentrate the data points around their cluster centers, using an appropriate potential.
Blekas, K. +2 more
openaire +2 more sources
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang +12 more
wiley +1 more source
Spectral clustering for TRUS images
Background Identifying the location and the volume of the prostate is important for ultrasound-guided prostate brachytherapy. Prostate volume is also important for prostate cancer diagnosis.
Salama Magdy MA, Mohamed Samar S
doaj +1 more source
Comparative analysis of chloroplast genomes from 14 genera of Thymelaeaceae revealed variation in gene content, ranging from 128 to 142 genes, primarily influenced by IR expansion/contraction events and pseudogenization of ndhF, ndhI, and ndhG. Two large inversions were detected within the large single‐copy region, including a synapomorphic inversion ...
Abdullah +8 more
wiley +1 more source
Joint Spectral–Spatial Representation Learning for Unsupervised Hyperspectral Image Clustering
Hyperspectral image (HSI) clustering has attracted significant attention due to its broad applications in agricultural monitoring, environmental protection, and other fields.
Xuanhao Liu, Taimao Wang, Xiaofeng Wang
doaj +1 more source

