Determining true genetic dissimilarity between individuals is an important and decisive point for clustering and analysing diversity within and among populations, because different dissimilarity indices may yield conflicting outcomes. We show that there are no acceptable universal approaches to assessing the dissimilarity between individuals with molecular markers. Different measures are releva...

Turnover (i.e., species substitution) and nestedness (i.e., subsets of species from more diverse locations), the two main mechanisms used to explain the beta diversity of biological communities, have different implications for biodiversity conservation. To better understand how these mechanisms contribute to beta diversity, we tested the following hypotheses: (i) greater dissimilarity in commun...

UNLABELLED ᅟ: There are many existing methodologies on measuring health equity, while seldom has method aiming at health resource allocation. We collected 6 method of measuring equity in health resource allocation. This paper presents key contents of methods on measuring horizontal equity in health service allocation, yet each method has its advantages and disadvantages as well as range of appl...

2 Abstract. Ecological studies have now gone beyond measures of species turnover towards measures of phylogenetic and functional dissimilarity. This change of perspective has a main objective: disentangling the processes that drive species distributions from local to broad scales. A fundamental difference between phylogenetic and functional analyses is that phylogeny is intrinsically dependent ...

Contemporary datasets are becoming increasingly larger and more complex, while techniques to analyse them are becoming more and more inadequate. Thus, new methods are needed to handle these new types of data. This study introduces methods to cluster histogram-valued data. However, histogram-valued data are difficult to handle computationally because observations typically have a different numbe...

Clustering on categorical data streams is a relatively new field that has not received as much attention as static data and numerical data streams. One of the main difficulties in categorical data analysis is lacking in an appropriate way to define the similarity or dissimilarity measure on data. In this paper, we propose three dissimilarity measures: a point-cluster dissimilarity measure (base...

Most clustering algorithmspartition a &fa set based on a dissimilarity relation expressed in t e m of some distance function. When the nature of this relation is conceptual rather than mehic, distance finctions may fail to adequately model dissimilarity. For this reason, we propose to extract dissimilarify relations directlyfrom the data. We exploit some pairs of paffems with known dissimilarit...

This paper focuses on the cell division cycle insuring the proliferation of cells and which is drastically aberrant in cancer cells. The aim of this biological problem is the identification of genes characterizing each cell cycle phase. The identification process is commonly based on a prior set of well-characterized cell cycle genes, called reference genes. The expression levels of the studied...