ii) is clustering of biological relevance, particularly in sensing and signalling?
In each cluster, significant variables are in descending order of relevance for the clustering process, based on statistical significance.
This has been used to derive a JIA interactome, and clusters of proteins of functional relevance.
Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA).
Clustering and the accuracy of clusters remain secondary issues to that of relevance when similarity approaches are explored in the context of biomedical literature [15], [16], [17].
Given its potential, a large number of research studies focus on several aspects of cluster analysis; for instance, clustering algorithms and extensions for particular data type [31], dissimilarity (or distance) metric [32], optimal cluster number [33], relevance of data attributes per cluster [34], evaluation of clustering results [35], and cluster ensembles [36].
For flood estimation and risk management, it is of relevance to understand whether clustering changes with flood severity and time scale.
We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes.
CIM is a visualisation tool that complements well the Correlation Circles plots and the Relevance Networks as clusters of subsets of variables of the same type correlated with subsets of variables of the other type can be observed.
Of relevance to this paper, Mahout supports a wide variety of clustering algorithms including: k-means, canopy clustering, fuzzy k-means, Dirichlet Clustering and Latent Dirichlet Allocation.
