Results 101 to 110 of about 178,314 (358)
Cloud Service Community Detection for Real-World Service Networks Based on Parallel Graph Computing
Heterogeneous information networks (e.g. cloud service relation networks and social networks), where multiple-typed objects are interconnected, can be structured by big graphs. A major challenge for clustering in such big graphs is the complex structures
Yu Lei, Philip S. Yu
doaj +1 more source
Oncogenic DMTF1β promotes cancer cell motility by regulating autophagy through ULK1 stabilization
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 +13 more
wiley +1 more source
Graph-based clustering and ranking for diversified image search
© 2014, Springer-Verlag Berlin Heidelberg. In this paper, we consider the problem of clustering and re-ranking web image search results so as to improve diversity at high ranks. We propose a novel ranking framework, namely cluster-constrained conditional
Liu, G +4 more
core +1 more source
A Unified Graph Theory Approach: Clustering and Learning in Criminal Data
Crime report clustering plays a critical role in modern law enforcement, enabling the identification of patterns and trends essential for proactive policing.
Haifa Al-Ibrahim, Heba Kurdi
doaj +1 more source
Tumor B‐cell infiltration in platinum‐treated advanced muscle‐invasive urothelial carcinoma
Bladder tumors with higher pretreatment memory B‐cell infiltration were linked to longer survival after cisplatin chemotherapy, but not carboplatin. These tumors also showed more organized immune structures (tertiary lymphoid structures) and a shared pro‐inflammatory B‐cell‐rich community, suggesting that memory B cells may help identify patients most ...
Konrad Stawiski +10 more
wiley +1 more source
Automatic Graph Clustering (System Demonstration)
We present a new, easy to understand algorithm and programming environment allowing for the interactive or automatic clustering of graphs according to several heuristics.
Sablowski, Reinhard +3 more
core +1 more source
Weakening the nuclear envelope: Lamin B receptor in melanoma metastasis
LBR‐driven nuclear fragility supports melanoma invasion. A: Melanocyte presents low LBR (Lamin B Receptor) levels, maintaining nuclear integrity and lamina‐chromatin tethering. B: During malignant progression, upregulation of LBR clusters at the INM (Inner Nuclear Membrane) during confined migration causes local lamina weakening and cholesterol ...
Francesca Lorenzini +1 more
wiley +1 more source
Clustering and domination in perfect graphs
A K-Cluster in a graph is an induced sub graph on k-vertices, which maximizes the number of edges. Both the K-Cluster problem and the K-dominating set problem are NP-complete for graphs in general. In this paper we investigate the complexity status of these problems on various subclasses of perfect graphs. In particular, we examine comparability graphs,
Derek G. Corneil, Yehoshua Perl
openaire +1 more source
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski +12 more
wiley +1 more source
Bayesian Methods for Graph Clustering [PDF]
Networks are used in many scientific fields such as biology, social science, and information technology. They aim at modelling, with edges, the way objects of interest, represented by vertices, are related to each other. Looking for clusters of vertices, also called communities or modules, has appeared to be a powerful approach for capturing the ...
Latouche, Pierre +2 more
openaire +3 more sources

