Expertise

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

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Searched keyword : Web development

Related people (7)

Etienne KORNOBIS

Group : FUNGEN - Embedded : 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.


Keywords
Data managementData VisualizationSequence analysisTranscriptomicsWeb developmentGenome analysisProgram developmentExploratory data analysisSofware development and engineeringGeneticsEvolutionRead mappingWorkflow and pipeline developmentPopulation geneticsMotifs and patterns detectionGrid and cloud computing
Organisms
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.


Keywords
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
Organisms

Projects (9)

Damien MORNICO

Group : FUNGEN - Hub Core

Graduated in “Structural Genomics and Bioinformatics”, I mainly worked during almost 6 years at the Genoscope (CEA) in the LABGeM team, within the microbial annotation platform MicroScope. I specifically focused on functional annotation and microbial metabolic pathways prediction and reconstruction, through pipeline implementation, database modeling and web interface development. Broadly, interactions in the MicroScope platform allowed me to tackle the whole annotation process: from genome assembly and gene prediction to network reconstruction. I also performed several comparative genomics analyses. As a member of the “Hub team”, I now take part to various projects, linked to HTS data, on different subjects (lncRNAs and stem cells, HIV integration and DNA structure, Ribosomal protein genes and genome evolution, Natural Antisense Transcripts in compact genomes…).


Keywords
Data managementGenomicsSequence analysisWeb developmentDatabaseGenome analysisDatabases and ontologiesOrthology and paralogy analysisRead mappingSequence homology analysisGene prediction
Organisms

Projects (14)

Rachel TORCHET

Group : WINTER - Hub Core

In 2012 I completed my master degree at the MicroScope Platform located at Genoscope (the French National Sequencing Center). I was involved in a project aiming at the management of evolution projects which rely on the Next Generation Sequencing (NGS) technologies to try to decipher the dynamics of genomic changes as well as the molecular bases and the mechanisms underlying adaptative evolution of micro-organisms (Remigi et al. 2014). Since November 2014, I joined the Bioinformatics and Biostatistics HUB at Institut Pasteur. I participated to the creation and updates of the C3BI website. I joined the WINTER group where I’m in charge of web and interface development projects. I have completed an UX-Design training to add extra value to my front-end development skills. I design and develop bioinformatics tools and interfaces that are users oriented.


Keywords
Data VisualizationWeb developmentDatabaseGenome analysisScientific computingDatabases and ontologiesSofware development and engineeringWorkflow and pipeline development
Organisms

Projects (5)

Related projects (13)

JASS: an online tool for the joint analysis of GWAS summary statistics

In recent years, large genome-wide association studies (GWAS) have been successful in identifying thousands of significant genetic associations for multiple traits and diseases1. In the course of this endeavor, sample size has proven to be the key factor for identifying new variants. For example, GWAS of body mass index (BMI), now including up to 350,000 individuals from more than 100 cohorts, have been able to identify genetic variant that explain as low as 0.02% of BMI variance2. While standard approaches for detecting new genetic variants associated with traits and diseases will go on as sample size increases, multivariate analyses have been proposed as an alternative strategy for both improving detection of new variants and exploring the multidimensional components of complex traits and diseases. Intuitively, multivariate analysis can be used to improve detection of variants displaying a pleiotropic effect3 by accumulating moderate evidence of association across multiple traits and diseases. Several recent examples have been published about not only GWAS hit overlap across related traits4, but also of genome-wide shared genetic effect5. Multivariate analyses of GWAS have also proven useful to understand shared genetics between diseases5, and potential causal relationship between phenotypes using Mendelian randomization (MR)6. Importantly, most of existing multivariate methods are based on GWAS summary statistics, while approaches based on individual-level data have been seldom considered because of major practical and ethical issues. In the continuity of ongoing work on multi-phenotype analysis (Aschard et al 20147, Aschard et al 20158), we developed an effective and robust multivariate approach of GWAS summary statistics that addresses the major barriers of existing approaches, i.e. the presence of correlation between studies that would exists when GWAS analyzed share sample9-16. Our approach consists in a robust omnibus multivariate test of GWAS summary statis



Project status : Awaiting Publication