Figure 13From: Nonlinear gene cluster analysis with labeling for microarray gene expression data in organ developmentplot of connectivity scores in increasing order for LE weights, LE cluster 22 We aim to further improve the biological specificity of cluster 22 derived from Laplacian Eigenmaps + k-means. To identify co-varying genes with high connectivity in the regulatory network of cluster 22, we measure connectivity by means of the weight matrix D in (2). The connectivity of Affymetrix probes within LE+KM cluster 22 are shown. The most highly connected genes in cluster 22 are Etv3, Zfp386, Kdm4c, Eea1, Fyttd1, which can be used as labels in Schroedinger Eigenmaps.Back to article page