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The weighted CSP framework is a soft constraint framework with a wide range of applications. Most current state-of-the-art complete solvers can be described as a basic depth-first branch and bound search that maintain some form of arc consistency during the search. In this paper we introduce a new stronger form of arc consistency, that we call exis-tential(More)
While the long noncoding RNAs (ncRNAs) constitute a large portion of the mammalian transcriptome, their biological functions has remained elusive. A few long ncRNAs that have been studied in any detail silence gene expression in processes such as X-inactivation and imprinting. We used a GENCODE annotation of the human genome to characterize over a thousand(More)
a r t i c l e i n f o a b s t r a c t The Valued Constraint Satisfaction Problem (VCSP) is a generic optimization problem defined by a network of local cost functions defined over discrete variables. It has applications in Artificial Intelligence, Operations Research, Bioinformatics and has been used to tackle optimization problems in other graphical models(More)
Optimizing a combination of local cost functions on discrete variables is a central problem in many formalisms such as in probabilistic networks, maximum satisfiabil-ity, weighted CSP or factor graphs. Recent results have shown that maintaining a form of local consistency in a Branch and Bound search provides bounds that are strong enough to solve many(More)
Mapping short reads against a reference genome is classically the first step of many next-generation sequencing data analyses, and it should be as accurate as possible. Because of the large number of reads to handle, numerous sophisticated algorithms have been developped in the last 3 years to tackle this problem. In this article, we first review the(More)
The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving problems involving both hard constraints and cost functions. It has been applied to various problems, including resource allocation, bioinformatics, scheduling, etc. To solve such problems, solvers usually rely on branch-and-bound algorithms equipped with local(More)
We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the(More)
The weighted constraint satisfaction problem (WCSP) is a soft constraint framework with a wide range of applications. Most current complete solvers can be described as a depth-first branch and bound search that maintains some form of local consistency during the search. However, the known consistencies are unable to solve problems with huge domains because(More)
Following recent discoveries about the important roles of non-coding RNAs (ncRNAs) in the cellular machinery, there is now great interest in identifying new occurrences of ncRNAs in available genomic sequences. In this paper, we show how the problem of finding new occurrences of characterized ncRNAs can be modeled as the problem of finding all(More)
High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological(More)