MOTIVATION The innovation of restriction-site associated DNA sequencing (RAD-seq) method takes full advantage of next-generation sequencing technology. By clustering paired-end short reads into groups with their own unique tags, RAD-seq assembly problem is divided into subproblems. Fast and accurately clustering and assembling millions of RAD-seq reads with sequencing errors, different levels o...

The augmented graph model, as introduced by Kleinberg (STOC 2000), is an appealing model for analyzing navigability in social networks. Informally, this model is defined by a pair (H,φ), where H is a graph in which inter-node distances are supposed to be easy to compute or at least easy to estimate. This graph is ”augmented” by links, called long range links, which are selected according to the...

This paper presents a fast simulated annealing framework for combining multiple clusterings (i.e. clustering ensemble) based on some measures of agreement between partitions, which are originally used to compare two clusterings (the obtained clustering vs. a ground truth clustering) for the evaluation of a clustering algorithm. Though we can follow a greedy strategy to optimize these measures a...

We introduce a multidimensional multiblock clustering (MDMBC) algorithm in this paper. MDMBC can generate overlapping clusters with similar values along of dimensions. The parsimonious binary vector representation lends itself to the application efficient meta-heuristic optimization algorithms. In paper, hill-climbing (HC) greedy search has been presented that be extended by several stochastic ...

MOTIVATION Genome analysis suggests that tandem duplication is an important mode of evolutionary novelty by permitting one copy of each gene to drift and potentially to acquire a new function. With more and more genomic sequences available, reconstructing duplication history has received extensive attention recently. RESULTS An efficient method is presented for inferring the duplication histo...

This paper proposes an attribute clustering algorithm for grouping attributes into clusters so as to obtain meaningful modes from microarray data. First the problem of attribute clustering is analyzed and neighborhood mutual information is introduced to solve it. Furthermore, an attribute clustering algorithm is presented for grouping attributes into clusters through optimizing a criterion func...

traditional leveraging statistical methods for analyzing today’s large volumes of spatial data have high computational burdens. to eliminate the deficiency, relatively modern data mining techniques have been recently applied in different spatial analysis tasks with the purpose of autonomous knowledge extraction from high-volume spatial data. fortunately, geospatial data is considered a proper s...

Iterative approximation algorithms are successfully applied in parametric approximation tasks. In particular, reduced basis methods make use of the so called Greedy algorithm for approximating solution sets of parametrized partial differential equations. Recently, a-priori convergence rate statements for this algorithm have been given (Buffa et al 2009, Binev et al. 2010). The goal of the curre...