The matrix of evolutionary distances is a model-based statistic, derived from molecular sequences, summarizing the pairwise phylogenetic relations between a collection of species. Phylogenetic tree reconstruction methods relying on this matrix are relatively fast and thus widely used in molecular systematics. However, because of their intrinsic reliance on summary statistics, distance-matrix me...

It is proposed that the co-expression of statistically significant motifs among the sequences of a proteome is a phylogenetic trait. From the co-expression matrix of such motifs in a group of prokaryotic proteomes a suitable definition of a phylogenetic distance is introduced and the corresponding distance matrix between proteomes is constructed. From the distance matrix a phylogenetic tree is ...

Concept hierarchies are important in many generalized data mining applications, such as multiple level association rule mining. In literature, concept hierarchy is usually given by domain experts. In this paper, we propose algorithms to automatically build a concept hierarchy from a provided distance matrix. Our approach is modifying the traditional hierarchical clustering algorithms. For the p...

For two integral histograms r = (r1, . . . , rd) and c = (c1, . . . , cd) of equal sum N , the MongeKantorovich distance dMK(r, c) between r and c parameterized by a d × d distance matrix T is the minimum of all costs < F, T > taken over matrices F of the transportation polytopeU(r, c). Recent results suggest that this distance is not negative definite, and hence, through Schoenberg’s well-know...

The aim of the present paper is to show how evolutionary algorithms can be applied to protein folding prediction. We start reviewing previous similar approaches that we criticize emphasizing the key issue of representation. A new evolutionary algorithm is described, based on the notion of distance matrix representation, together with a software package that implements it. Finally, experimental ...

The distance energy of a graph G is a recently developed energy-type invariant, defined as the sum of absolute values of the eigenvalues of the distance matrix of G. There was a vast research for the pairs and families of non-cospectral graphs having equal distance energy, and most of these constructions were based on the join of graphs. A graph is called circulant if it is Cayley graph on the ...

Abstract—Alignment of biological sequences such as DNA, RNA or proteins is one of the most widely used tools in computational bioscience. One of the important research topics of bioinformatics is the multiple proteins sequence alignment. Since the exact methods for MSA have exponential time complexity, the heuristic approaches and the progressive alignment are the most commonly used in multiple...

We present the cosmological distance errors achievable using the baryon acoustic oscillations as a standard ruler. We begin from a Fisher matrix formalism that is upgraded from Seo & Eisenstein (2003). We isolate the information from the baryonic peaks by excluding distance information from other less robust sources. Meanwhile we accommodate the Lagrangian displacement distribution into the Fis...

In general, the similarity measure is indispensable for most traditional spectral clustering algorithms since these algorithms typically begin with the pairwise similarity matrix of a given dataset. However, a general type of input for most clustering applications is the pairwise distance matrix. In this paper, we propose a distance-based spectral clustering method which makes no assumption on ...

project selection is considered as an important problem in project management. it is multi-criteria in nature and is based on various quantitative and qualitative factors. the main purpose of this paper is to present a new rank-based method for project selection in outranking relation. according to this approach, decision alternatives were clustered in the concordance matrix and the discordance...