Weighted correlation network analysis, also known as weighted gene co-expression network analysis (WGCNA), is a widely used data mining method especially...

accurate molecular biomarker of aging, and for developing weighted correlation network analysis. His work on the genomic biomarkers of aging, the aging...

constructing and analyzing weighted networks in particular weighted correlation networks. Disparity filter algorithm of weighted network Wasserman, S., Faust...

Biological network inference Biostatistics Computational biology Systems biology Weighted correlation network analysis Interactome Network medicine Ecological...

Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures...

known pathway members. Weighted correlation network analysis Gene regulatory networks Biological network inference Biological network Stuart, Joshua M; Segal...

evaluating similarity in gene expression networks, and is often used for weighted correlation network analysis. Biweight midcorrelation has been implemented...

Sufficient dimension reduction Topological data analysis Weighted correlation network analysis Factor analysis van der Maaten, Laurens; Postma, Eric; van den...

system. Weighted graphs that blend an abstract understanding of complex network theories and electric power systems properties. Social network analysis examines...

commercial suits; network-based approaches for analyzing high dimensional genomic data sets. For example, weighted correlation network analysis is often used...

system, semantic networks, and functional brain networks. In the case of network activity, the analysis is based on partial correlations. In simple words...

spatial neural networks, but they do not consistently handle the spatial heterogeneity at multiple scales. Geographically Weighted Neural Networks (GWNNs) are...

Components" which are, actually, the eigenvectors of the data correlation matrix weighted by the inverse of their eigenvalues. This change of variables...

For a meta-analysis of correlational data, effect size information is usually collected as Pearson's r statistic. Partial correlations are often reported...

calibration problem Cancer cluster Candlestick chart Canonical analysis Canonical correlation Canopy clustering algorithm Cantor distribution Carpet plot...

523–41. Julian C. Stanley, "II. Analysis of Variance," pp. 541–554. Lindley, D.V. (1987). "Regression and correlation analysis," New Palgrave: A Dictionary...

Yang JJ, Chen S, et al. (January 2018). "Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design". Scientific Reports. 8 (1):...

and performance profiling of network inference methods. WGCNA is an R package for weighted correlation network analysis. Pigengene is an R package that...

"error" terms, hence factor analysis can be thought of as a special case of errors-in-variables models. The correlation between a variable and a given...

regarding its methodology. These criticisms led to the use of the correlation-weighted Kolmogorov–Smirnov test, the normalized ES, and the false discovery...

Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press. Tore Opsahl & Pietro Panzarasa (2009). "Clustering in Weighted Networks"...

neurons to become the input of others. The network forms a directed, weighted graph. An artificial neural network consists of simulated neurons. Each neuron...

such a network architecture does not take the spatial structure of the data into account. Convolutional networks exploit spatially local correlation by enforcing...

graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications...

West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences Archived 2024-10-04 at the Wayback Machine...

of a slightly different matrix. PCA is also related to canonical correlation analysis (CCA). CCA defines coordinate systems that optimally describe the...

inputs to redistribute those effects to each target output. Often, a correlation-style matrix of dot products provides the re-weighting coefficients....

; Yao, X. (December 1999). "Ensemble learning via negative correlation". Neural Networks. 12 (10): 1399–1404. doi:10.1016/S0893-6080(99)00073-8. ISSN 0893-6080...

scores. In the informal model, responses are also weighted, using a linear model. When factoring a correlation matrix, the estimated answers appear as the first...

methods of analysis focus either on independent components or on regions of correlation.[citation needed] Independent component analysis (ICA) is a useful...