Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise

Search by keywords | Search by organisms

Searched keyword : Motifs and patterns detection

Related people (3)


Group : GENO - Hub Core

2015 – . – Institut Pasteur, Paris, France – Unit : Bioinformatics and Biostatistics HUB 2012 – 2015 – Institut Pasteur, Paris, France – Unit : Molecular Genetics of Yeasts Supervisor : Prof. B. Dujon 2012 – Institut Pasteur, Paris, France – Unit : Integrated Mycobacterial Pathogenomics Supervisor: Dr. R. Brosch Education 2012– MSc. Bioinformatics – Université Paris Diderot (Paris VII)

Genome assemblySequence analysisGenome analysisOrthology and paralogy analysisRead mappingSequence homology analysisDNA structure analysisGenome rearrangementsMotifs and patterns detection
Saccharomyces cerevisiae
Projects (24)


Group : PLATEFORM - Detached : Epigenetic regulation

After a PhD in Biology in 2011 on population genetics and phylogeography on amazing little amphipods (Crangonyx, Crymostygius) at the University of Reykjavik (Iceland), I pursued my interest in Bioinformatics and Evolutionary Biology in various post-docs in Spain (MNCN Madrid, UB Barcelona). During this time, I investigated transcriptomic landscapes for various non-model species (groups Conus, Junco and Caecilians) using de novo assemblies and participated in the development of TRUFA, a web platform for de novo RNA-seq analysis. In July 2016, I integrated the Revive Consortium and the Epigenetic Regulation unit at Pasteur Institute, where my main focus were transcriptomic and epigenetic analyses on various thematics using short and long reads technologies, with a special interest in alternative splicing events detection. I joined the Bioinformatics and Biostatistics Hub in January 2018. My latest interests are long reads technologies, alternative splicing and achieving reproducibility in Bioinformatics using workflow managers, container technologies and literate programming.

Data managementData VisualizationSequence analysisTranscriptomicsWeb developmentGenome analysisProgram developmentExploratory data analysisSofware development and engineeringGeneticsEvolutionRead mappingWorkflow and pipeline developmentPopulation geneticsMotifs and patterns detectionGrid and cloud computing
HumanInsect or arthropodOther animalAnopheles gambiae (African malaria mosquito)Mouse
Projects (3)

Christophe MALABAT

Group : HEAD - Hub Core

After a PhD in biochemistry of the rapeseed proteins, during which I developed my first automated scripts for handling data processing and analysis, I join Danone research facility center for developing multivariate models for the prediction of milk protein composition using infrared spectrometry.
As I was already developing my own informatics tools, I decided to join the course of informatic for biology of the Institut Pasteur in 2007. At the end of the course I was recruited by the Institute and integrate the unit of “génétique des interactions macromoléculaires” of Alain Jacquier. Within this group, I learn to handle sequencing data and I developed processing and analysis tools using python and R. I also create a genome browser and database system for storing, retrieving and visualizing microarray data. After 8 years within the Alain Jacquier’s lab, I join the Hub of bioinformatics and biostatistics as co-head of the team.

ClusteringData managementSequence analysisTranscriptomicsWeb developmentDatabaseGenome analysisProgram developmentScientific computingExploratory data analysisData and text miningIllumina HiSeqRead mappingLIMSIllumina MiSeqHigh Throughput ScreeningMultidimensional data analysisWorkflow and pipeline developmentRibosome profilingMotifs and patterns detection

Projects (10)

Related projects (3)


African trypanosomes are transmitted by the bite of the tsetse fly and cause the debilitating, and often fatal, neglected tropical disease sleeping sickness, or Human African Trypanosomiasis (HAT). Trypanosoma brucei gambiense, the parasites responsible for 98% of human cases, first reside in the patient blood and skin for months to years before invading the central nervous system, where they cause the neurological symptoms of the disease. HAT is approaching elimination, with the number of cases reported in 2017 dropping to approximately 1,442 from only a dozen African countries. In this context, HAT was included in the WHO roadmap on neglected tropical diseases, with 2020 set as target date for elimination as a public health problem. A secondary goal of zero transmission by 2030 has also been set. These targets have, in part, been encouraged by the success of surveillance efforts that rely on detecting extracellular trypanosomes in human blood. Nevertheless, the reduction in case numbers brings about other challenges. For example, the sensitivity of any diagnostic test diminishes as the disease burden drops, and this is being seen with the serological tests available for HAT. In this context, new highly sensitive and specific diagnostic tools will be required to accurately monitor the occurrence of new cases and the possible emergence of drug-resistant trypanosomes during the elimination phase. Most diagnostic tests currently under development are based on optimization of existing methods that may not combine all the requirements to stand up to the harsh constraints imposed by the elimination phase requirements, especially in terms of sensitivity and specificity. We propose that adapting the recently developed Specific High-sensitivity Enzymatic Reporter unLOCKing (SHERLOCK) technology that combines a CRISPR-Cas system and lateral flow test to trypanosomes will provide the sensitivity and specificity required for a diagnostic test in the elimination and post elimination phases. The SHERLOCK system relies on the collateral effect of Cas13a promiscuous RNA cleavage activity upon target recognition. Combining the collateral effect with pre-amplification of RNAs resulted in rapid RNA detection with attomolar (10^-18 moles/l) sensitivity and single-base mismatch specificity, in a diagnostic setting. This technology has been used to detect specific strains of Zika and Dengue viruses and distinguish pathogenic bacteria in a mixed sample. Furthermore, SHERLOCK reaction reagents can be lyophilized for cold-chain independence and long-term storage and be readily reconstituted on paper for field applications. A lateral flow test for a simple and rapid readout can be easily implemented after a reaction that does not exceed two hours from the sampling step. The first step of this project is to identify promising RNA targets in silico by data mining and multiple alignements of all available transcriptomic data on bloodstream African trypanosomes.

Project status : Closed