Results 151 to 160 of about 940,524 (345)
Molecular Oncology, EarlyView.Beyond its role in immune evasion, this study identified that CD47 drives tumor‐intrinsic signaling in non‐small cell lung cancer (NSCLC). Transcriptomic profiling and functional studies revealed that CD47 regulates cell adhesion, migration, and metastasis through an ERK–EMT signaling axis.
Asa P.Y. Lau +8 more
wiley +1 more source
$Ibk$-means: An iterative batch $k$-means algorithm for big data clustering [PDF]
summary:Information technologies such as social media, mobile computing, and the realization of the industrial Internet of Things (IoT) produce huge amounts of data every day.
Alguliyev, Rasim +3 more
core +1 more source
Molecular Oncology, EarlyView.We analyze cisplatin–DNA adducts (CDAs) and double‐strand breaks (DSBs) in a cell‐cycle‐dependent manner. We find that CDAs form similarly across all cell cycle phases. DSBs arise only in S‐phase. CDAs might not directly impair DSB repair, but S‐phase DSB lesions evolve in the presence of CDAs and disrupt repair in G2, also causing radiosensitization ...
Ye Qiu +10 more
wiley +1 more source
Molecular Oncology, EarlyView.RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner +14 more
wiley +1 more source
Molecular Oncology, EarlyView.CIN85 is highly expressed in osteosarcoma, particularly in metastatic lesions. Its overexpression increases cell migration and Matrigel invasion, while silencing CIN85 suppresses these behaviors. Transcriptome analysis shows that CIN85 regulates MMP2, COL3A1, and Akt/mTOR signaling. Targeting these pathways reverses CIN85‐induced motility, highlighting
Iryna Horak +10 more
wiley +1 more source
A rate of convergence in clustering analysis. [PDF]
We present a result about stochastic boundedness of stable empirical processes on Vapnik-Cervonenkis classes of functions and we apply it to obtain a rate of convergence for the approximation between the sample and the populational variation in the k ...
Romo, Juan
core
An Efficient k-modes Algorithm for Clustering Categorical Datasets
, 2020 Mining clusters from datasets is an important endeavor in many applications. The k-means algorithm is a popular and efficient distribution-free approach for clustering numerical-valued data but can not be applied to categorical-valued observations. The k-
Maitra, Ranjan, Dorman, Karin
core
A Binary Linear Programming-Based K-Means Approach for the Capacitated Centered Clustering Problem
, 2019 The k-means algorithm is one of the most popular clustering algorithms in the machine learning community. Its simplicity and scalability make it the primary choice for many clustering applications. We introduce here a variant of the kmeans algorithm that
Baumann, Philipp, Philipp Baumann
core +1 more source
We present a \(k\)-means-based clustering algorithm, which optimizes the mean square error, for given cluster sizes. A straightforward application is balanced clustering, where the sizes of each cluster are equal. In the \(k\)-means assignment phase, the algorithm solves an assignment problem using the Hungarian algorithm.
Mikko I. Malinen, Pasi Fränti
openaire +2 more sources
Molecular Oncology, EarlyView.Circulating tumor cells (CTCs) and plasma cell‐free DNA (cfDNA) were analyzed to detect ESR1 mutations and methylation in patients with advanced breast cancer. CTC‐derived DNA showed higher sensitivity for mutation detection and revealed complementary genetic and epigenetic alterations, highlighting the added value of CTC analysis for understanding ...
Dimitra Stergiopoulou +12 more
wiley +1 more source