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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)
Plants have evolved efficient defence mechanisms to defend themselves from pathogen attack. Although many studies have focused on the transcriptional regulation of defence responses, less is known about the involvement of microRNAs (miRNAs) as post-transcriptional regulators of gene expression in plant immunity. This work investigates miRNAs that are(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)
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)
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)
MOTIVATION Recent technological advances are allowing many laboratories to sequence their research organisms. Available de novo assemblers leave repetitive portions of the genome poorly assembled. Some genomes contain high proportions of transposable elements, and transposable elements appear to be a major force behind diversity and adaptation. Few de novo(More)
By representing the constraints and objective function in factorized form, graphical models can concisely define various NP-hard optimization problems. They are therefore extensively used in several areas of computer science and artificial intelligence. Graphical models can be deterministic or stochastic, optimize a sum or product of local functions,(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)