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...

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

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

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

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

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

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

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

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

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

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

ISSN 0096-851X. Tryon, Robert C. (1939). Cluster Analysis: Correlation Profile and Orthometric (factor) Analysis for the Isolation of Unities in Mind and Personality...

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

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

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

site-site correlations. John Hopfield popularised this architecture in 1982, and it is now known as a Hopfield network. The time delay neural network (TDNN)...

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

intercrosses and heterogeneous stock Weighted correlation network analysis, also known as WGCNA Cytoscape network display Correlated trait loci mapping...

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):...

to interpret neural network results by analysis of correlations between data cases in the space of models. A physical neural network includes electrically...

and procedures are: Analysis of variance (ANOVA) Chi-squared test Correlation Factor analysis Mann–Whitney U Mean square weighted deviation (MSWD) Pearson...

semantic networks. In the case of network activity, the analysis is based on partial correlations. In simple words, the partial (or residual) correlation is...

that the network does not have a characteristic scale or "size". Many networks have been reported to be scale-free, although statistical analysis has refuted...

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

denoising step. In DART, a weighted average is used where the weights reflect the degree of the nodes in the pruned network. The denoising step removes...

Canonical correlation analysis (CCA) Factor analysis Feature extraction Feature selection Independent component analysis (ICA) Linear discriminant analysis (LDA)...

techniques to learn the conceptual correlations in a collection of text. In general, the process involves constructing a weighted term-document matrix, performing...

that since h-index is a cumulative measure, it contains intrinsic auto-correlation that led to significant overestimation of its predictability. Thus, the...