Results 71 to 80 of about 572,176 (269)
Bivariate correlation coefficients in family‐type clustered studies [PDF]
Biometrical Journal, 2015 We propose a unified approach based on a bivariate linear mixed effects model to estimate three types of bivariate correlation coefficients (BCCs), as well as the associated variances between two quantitative variables in cross‐sectional data from a family‐type clustered design. These BCCs are defined at different levels of experimental units including
Luo, Jingqin +4 more
openaire +2 more sources
Molecular Oncology, EarlyView.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
Cell surface interactome analysis identifies TSPAN4 as a negative regulator of PD‐L1 in melanoma
Molecular Oncology, EarlyView.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
Curvature of Indoor Sensor Network: Clustering Coefficient
EURASIP Journal on Wireless Communications and Networking, 2008 We investigate the geometric properties of the communication graph in realistic low-power wireless networks. In particular, we explore the concept of the curvature of a wireless network via the clustering coefficient. Clustering coefficient analysis is a
Ariaei F +4 more
doaj
LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro
Molecular Oncology, EarlyView.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
A Name Recognition Method Based on Clustering Coefficient [PDF]
Jisuanji gongcheng, 2016 In many application fields of Chinese text analysis, name recognition is a widespread fundamental issue. Although there are several kinds of name recognition methods, they are mainly based on corpus statistics and language rules.
ZENG Jianping,LIU Hua
doaj +1 more source
Clustering of correlated networks
, 2003 We obtain the clustering coefficient, the degree-dependent local clustering, and the mean clustering of networks with arbitrary correlations between the degrees of the nearest-neighbor vertices. The resulting formulas allow one to determine the nature of
Dorogovtsev, S. N.
core +1 more source
Corrected Overlap Weight and Clustering Coefficient [PDF]
, 2019 The paper is a detailed and extended version of the talk presented at the CMStatistics (ERCIM) 2015 ...
openaire +2 more sources
Molecular Oncology, EarlyView.To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source
Molecular Oncology, EarlyView.Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley +5 more
wiley +1 more source