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Biomedical subjects

Gregory Nuel

Publications and source records attributed to Gregory Nuel.

3 recordsLinked to original sources

Numerical solutions for patterns statistics on Markov chains.

We propose here a review of the methods available to compute pattern statistics on text generated by a Markov source. Theoretical, but also numerical aspects are detailed for a wide range of techniques (exact, Gaussian, large deviations, binomial and compound Poisson). The SPatt package (Statistics for Pattern, free software available at http://stat.genopole.cnrs.fr/spatt) implementing all these methods is then used to compare all these approaches in terms of computational time and reliability in the most complete pattern statistics benchmark available at the present time.

Algorithms↗

Detecting local high-scoring segments: a first-stage approach for genome-wide association studies.

Genetic epidemiology aims at identifying biological mechanisms responsible for human diseases. Genome-wide association studies, made possible by recent improvements in genotyping technologies, are now promisingly investigated. In these studies, common first-stage strategies focus on marginal effects but lead to multiple-testing and are unable to capture the possibly complex interplay between genetic factors. We have adapted the use of the local score statistic, already successfully applied to analyse long molecular sequences. Via sum statistics, this method captures local and possible distant dependences between markers. Dedicated to genome-wide association studies, it is fast to compute, able to handle large datasets, circumvents the the multiple-testing problem and outlines a set of genomic regions (segments) for further analyses. Applied to simulated and real data, our approach outperforms classical Bonferroni and FDR corrections for multiple-testing. It is implemented in a software termed LHiSA for Local High-scoring Segments for Association and available at: http://stat.genopole.cnrs.fr/software/lhisa.

Algorithms↗

Short inverse complementary amino acid sequences generate protein complexity.

Inversions of short genomic sequences play a central role in the generation of protein complexity. More than half of the 1300 motifs registered in ProSite have protein inverse complementary sequences (princoms) among proteins registered in SwissProt. The observed number of princoms occurrences exceeds by far the expected number (p < 10(-10)). Princoms often endow their host proteins with a whole new range of biochemical and physiological capabilities, including the possibility of intramolecular and intermolecular disulfide bond formation. These results support the idea that, like the duplications, the inversions of small genomic fragments have been a fundamental mechanism for shaping genomes.

Amino Acid Motifs↗