Estadística Aplicada a los Recursos Marinos. Clustering. Análisis de segmentación

Introducción al análisis con Clustering

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Competing Lipid-Protein and Protein-Protein Interactions Determine Clustering and Gating Patterns in the Potassium Channel from Streptomyces lividans (KcsA)

There is increasing evidence to support the notion that membrane proteins, instead of being isolated components floating in a fluid lipid environment, can be assembled into supramolecular complexes that take part in a variety of cooperative cellular functions. The interplay between lipid-protein and protein-protein interactions is expected to be a determinant factor in the assembly and dynamics of such membrane complexes. Here we report on a role of anionic phospholipids in determining the extent of clustering of KcsA, a model potassium channel. Assembly/disassembly of channel clusters occurs, at least partly, as a consequence of competing lipid-protein and protein-protein interactions at nonannular lipid binding sites on the channel surface and brings about profound changes in the gating properties of the channel. Our results suggest that these latter effects of anionic lipids are mediated via the Trp67–Glu71–Asp80 inactivation triad within the channel structure and its bearing on the selectivity filter.