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 (8)

Etienne KORNOBIS

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.


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 (10)

Fabien MAREUIL

Group : WINTER - Hub Core

After a Master degree in Genome Analysis and Molecular Modeling at Denis Diderot University, I did a PhD in NMR / bioinformatics at Denis Diderot University, where I worked on the development and use of a software named DaDiModO which uses SAXS data and RDC/NMR data to calculate models of structural proteins. After a postdoc aiming to adapt ARIA software to allow execution on computing grid in the Structural Bioinformatic Team at Institut Pasteur in collaboration with IBCP, I joined CIB/DSI Team where I was responsible for the development of bioinformatics projects and the deployment, maintenance and evolution of the Pasteur Galaxy server. I joined the Hub/C3BI team in 2017 as research engineer where I’m involved in several projects such as structural bioinformatics, softwares and web development. I am also in charge of the maintenance of the Galaxy Pasteur instance.


Keywords
Data managementGalaxyStructural bioinformaticsWeb developmentDatabaseProgram developmentScientific computingDatabases and ontologiesWorkflow and pipeline developmentGrid and cloud computing
Organisms
Non applicable
Projects (16)

Damien MORNICO

Group : SysBio - 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 (18)

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 (12)

Related projects (30)

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 : Closed

The Flemmingsome: the proteome of intact cytokinetic midbodies

The central part of the intercellular bridge connecting the two daughter cells during cytokinesis is a highly dense structure named the Midbody first described by Flemming in 1891. Work in the past ten years revealed that the midbody is a platform that concentrates essential proteins involved in cytokinetic abscission. After abscission, the midbody is cut on both sides, thus generating a midbody remnant (named MBR). The MBR usually interacts with the cell surface of one of the two daughter cells, before being engulfed in a phagocytic-like manner. We also found that the MBR can be easily released from cells before their engulfment by calcium chelation. Of note, MBRs at the cell surface might act as pro-proliferative, signalling entities but the proteins involved and the mechanisms of MBR anchoring are unknown. A previous proteomic study of the midbody conducted by Skop purified intercellular bridges from cell lysates recovered after cell synchronization, microtubule stabilization and detergent treatment. This pioneer proteomic study, although informative, did not allow the recovery of many key known proteins of the midbody. Here, we set up an experimental protocol to purify intact, detergent-free MBRs in order to have the full proteome of this organelle. Quantitative, label-free proteomics enabled us to identify 529 proteins enriched at least 2 times as compared to whole cell lysates, that we named the “Flemmingsome”. Besides known and well-established proteins of the midbody (MKLP1, MgcRacGAP, AuroraB, INCENP, MKLP2, Rab8, Rab11, Rab35, Citron Kinase, ESCRTs…), we identified new and promising candidates potentially involved in cytokinetic abscission. In addition, we identified 27 transmembrane proteins that are excellent candidates for mediating interactions between the MBR and the receiving daughter cells after cytokinetic abscission. We are also currently exploring whether newly identified candidates could participate in the signalling mediated by the MBRs. We would thus like to create a website that recapitulates the findings of our screen. The proteins discovered represent new candidates for the understanding of cytokinesis and tumorigenesis. This should be instrumental in the field as the previous websites are not updated (Microkits, Uniprot) and do not focus on this particular step of cytokinesis.



Project status : Closed

Pasteur MLST: Institut Pasteur genomic taxonomy database of microbial strains

- The Institut Pasteur genomic taxonomy database of microbial strains (“Pasteur MLST”) is a free, publicly-accessible resource that hosts nucleotide sequence-based definitions of microbial strains, along with information on bacterial isolates (provenance data) and their genomic sequences. The Pasteur MLST database provides universal nomenclatures that are largely adopted for important pathogens (Klebsiella, Listeria, …), and represent a unifying language on strains for microbial population biology. - Unified strain taxonomies facilitate the coordinated international surveillance of bacterial pathogens. Several hundred research laboratories and public health agencies worldwide have deposited novel strain types, sequences and provenance data on their bacterial isolates. - Pasteur MLST is powered by the Open source GPL3 BIGSdb web application developed at Oxford University (Keith Jolley & Martin Maiden). (http://bigsdb.pasteur.fr ). Its evolution in terms of functionality is tightly linked to the developments of the software at Oxford U. Its evolution in terms of contents is managed by dedicated international teams of curators for each bacterial pathogenic species, coordinated by the PasteurMLST team. - The genomic taxonomies hosted at Pasteur MLST represent unique, authoritative resources that are highly valued by the community, as testified by the routine use of Pasteur MLST strain tags (e.g., K. pneumoniae ST258) in the scientific literature. Several labs (National Reference Centers or Units) of Institut Pasteur are coordinating the curation of genomic taxonomies (Klebsiella, Listeria, Corynebacteria, Bordetella, Leptospira, Yersinia, ...). The aim of the project is to obtain support from the C3BI HUB for the maintenance of the BIGSdb instance at Pasteur: deployment, upgrades, installation of API functionality developed by our partner, coping with future IT evolutions, ...



Project status : In Progress

Development and design of new functionalities for MEMHDX, a web application dedicated to the statistical analysis and vizualization of large HDX-MS datasets.



Project status : In Progress

An integrated software having a graphical user interface for the analysis of time-lapse images of bacterial microcolonies



Project status : Closed

Development of a web server to calculate functional binding sites using Deep Learning



Project status : In Progress

Development of a secure API for ARIAweb



Project status : In Progress

An online database of RNA-small molecules complexes for rational drug design

The majority of approved drugs target proteins, which are encoded in a very small fraction of the human genome. When a pathology is associated with so-called undruggable proteins, an alternative strategy should be sought. In the last twenty years, non-coding RNA molecules have been shown to perform a variety of crucial biological functions, including regulating gene expression, protecting chromosomes from foreign nucleic acids, and guiding telomers synthesis. In this context, targeting either mRNA molecules that are translated into undruggable protein targets or biologically relevant non-coding RNA molecules with small molecules is emerging as a promising therapeutical approach in pathologies such as cancer, viral infections, and neurodegenerative disorders. However, the number of approved drugs that target RNA molecules is still very limited and the existing examples have mostly been found by costly and time-consuming screening experiments. In this project, we aim at building a computational framework to guide the rational design of drugs targeting RNA. To this end, we created a database containing all the experimentally-determined structures of RNA-small molecule complexes deposited in the PDB database. The entries containing drug-like compounds were selected and annotated based on the different biological entities interacting with the ligands. Our database, freely accessible via a web interface, will facilitate i) mapping the chemical space of the small molecules known to bind RNA, ii) understanding the nature of the interactions that drive ligand/RNA recognition, and iii) benchmarking existing tools for in silico protein drug design with RNA targets.



Project status : Closed