Philippe Rinaudo

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We present a general setting for structure-sequence comparison in a large class of RNA structures that unifies and generalizes a number of recent works on specific families on structures. Our approach is based on tree decomposition of structures and gives rises to a general parameterized algorithm, where the exponential part of the complexity depends on the(More)
High-throughput technologies such as transcriptomics, proteomics, and metabolomics show great promise for the discovery of biomarkers for diagnosis and prognosis. Selection of the most promising candidates between the initial untargeted step and the subsequent validation phases is critical within the pipeline leading to clinical tests. Several statistical(More)
We present a general setting for structure-sequence comparison in a large class of RNA structures that unifies and generalizes a number of recent works on specific families on structures. Our approach is based on tree decomposition of structures and gives rises to a general parameterized algorithm, where the exponential part of the complexity depends on the(More)
RNA molecules play major roles in all cell processes, and therefore have been subject to a great attention by biologists, biochemists and bioinformaticians in the recent years. From a computational optimization point of view, two interrelated major issues are on one hand the problem of structure prediction, and the problem of comparing two or several RNA(More)
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