Results 101 to 110 of about 761,172 (262)
Big data clustering with varied density based on MapReduce
The DBSCAN algorithm is a prevalent method of density-based clustering algorithms, the most important feature of which is the ability to detect arbitrary shapes and varied clusters and noise data. Nevertheless, this algorithm faces a number of challenges,
Safanaz Heidari +4 more
doaj +1 more source
Spectral density-based clustering algorithms for complex networks. [PDF]
Ramos TC, Mourão-Miranda J, Fujita A.
europepmc +1 more source
ERRFI1, a neural crest (NC)‐associated gene, was upregulated in melanoma and negatively correlated with the expression of melanocytic differentiation markers and the susceptibility of melanoma cells toward BRAF inhibitors (BRAFi). Knocking down ERRFI1 significantly increased the sensitivity of melanoma cells to BRAFi.
Nina Wang +8 more
wiley +1 more source
Zanthoxylum infructescence detection based on adaptive density clustering
Infructescence detection during the early fruiting stage is a necessary preliminary work to estimate the yield of Zanthoxylum. The purpose of this research is to detect and quantify the infructescences on the images of early fruit-bearing branches of ...
Diwei Wu +4 more
doaj +1 more source
Fast Density Based Clustering Algorithm
Clustering problem is an unsupervised learning problem. It is a procedure that partition data objects into matching clusters. The data objects in the same cluster are quite similar to each other and dissimilar in the other clusters. The traditional algorithms do not meet the latest multiple requirements simultaneously for objects.
Priyanka Trikha, Singh Vijendra
openaire +1 more source
CDK11 inhibition stabilises the tumour suppressor p53 and triggers the production of an alternative p21WAF1 splice variant p21L, through the inactivation of the spliceosomal protein SF3B1. Unlike the canonical p21WAF1 protein, p21L is localised in the cytoplasm and has reduced cell cycle‐blocking activity.
Radovan Krejcir +12 more
wiley +1 more source
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
Model-based Methods of Classification: Using the mclust Software in Chemometrics [PDF]
Due to recent advances in methods and software for model-based clustering, and to the interpretability of the results, clustering procedures based on probability models are increasingly preferred over heuristic methods. The clustering process estimates a
Adrian Raftery, Chris Fraley
core +1 more source
Liquid biopsy epigenetics: establishing a molecular profile based on cell‐free DNA
Cell‐free DNA (cfDNA) fragments in plasma from cancer patients carry epigenetic signatures reflecting their cells of origin. These epigenetic features include DNA methylation, nucleosome modifications, and variations in fragmentation. This review describes the biological properties of each feature and explores optimal strategies for harnessing cfDNA ...
Christoffer Trier Maansson +2 more
wiley +1 more source
Cytoplasmic p21 promotes stemness of colon cancer cells via activation of the NFκB pathway
Cytoplasmic p21 promotes colorectal cancer stem cell (CSC) features by destabilizing the NFκB–IκB complex, activating NFκB signaling, and upregulating BCL‐xL and COX2. In contrast to nuclear p21, cytoplasmic p21 enhances spheroid formation and stemness transcription factor CD133.
Arnatchai Maiuthed +10 more
wiley +1 more source

