Stéphane Schicklin

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UNLABELLED Pseudomonas aeruginosa is an antibiotic-refractory pathogen with a large genome and extensive genotypic diversity. Historically, P. aeruginosa has been a major model system for understanding the molecular mechanisms underlying type I clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR-associated protein (CRISPR-Cas)-based(More)
There is an increasing need in transcriptome research for gene expression data and pattern warehouses. It is of importance to integrate in these warehouses both raw transcriptomic data, as well as some properties encoded in these data, like local patterns. We have developed an application called SQUAT (SAGE Querying and Analysis Tools) which is available(More)
There is a critical need for new and efficient computational methods aimed at discovering putative transcription factor binding sites (TFBSs) in promoter sequences. Among the existing methods, two families can be distinguished: statistical or stochastic approaches, and combinatorial approaches. Here we focus on a complete approach incorporating a(More)
Research and development of innovative in-vitro diagnostic (IVD) solutions in infectious diseases require to federate up-to-date knowledge from several fields known for their complexity and their constant evolution: medical practices, microbiology and system and software engineering [6, 11, 12]. To tackle the inherent complexity of such multidisciplinary(More)
Genetic determinants of antibiotic resistance (AR) have been extensively investigated. High-throughput sequencing allows for the assessment of the relationship between genotype and phenotype. A panel of 672 Pseudomonas aeruginosa strains was analysed, including representatives of globally disseminated multidrug-resistant and extensively drug-resistant(More)
The increasing burden of multidrug-resistant bacteria affects the management of several infections. In order to prescribe adequate antibiotics, clinicians facing severe infections such as hospital-acquired pneumonia (HAP) need to promptly identify the pathogens and know their antibiotic susceptibility profiles (AST), which with conventional microbiology(More)
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