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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Related people (7)

Quentin GIAI

Group : - Hub Core


Keywords

Organisms

Projects (0)

    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
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    Projects (15)

    Bertrand NÉRON

    Group : ALPS - Hub Core

    Activities Contact for any subject related to IFB. Help scientists to develop new tools (architecture, design, implementation). animate the Python Working Group at pasteur . O|B|F (http://www.open-bio.org/) member. Skills Strong programming experience in Python. Software architecture and design. NoSQL DataBase (MongoDB, CouchDB) XML/YAML continuous integration (github/travis-CI/readthedocs, gitlab/gitlab-CI) containers (Docker, Singularity) linux (Gentoo, Xubuntu) IFB developer Main projects on the campus Mobyle http://Mobyle.pasteur.fr Mobyle: a new full web bioinformatics framework IntegronFinder (ongoing project) MacsyFinder (ongoing project) githubaccess to my projects on github Teaching Unix (Unix-I , Unix-II) Python . Education 2002 Phd in Molecular and cellular biology. “Rôle de deux protéines QN1 et PATF impliquées dans l’arrêt de prolifération des cellules de la neurorétine aviaire au cours du developpement”. 2001 “Informatique En Biologie” course (Pasteur)


    Keywords
    Data managementDatabaseProgram developmentScientific computingDatabases and ontologies
    Organisms
    Non applicable
    Projects (11)

    Louis JONES

    Group : SINGLE - Hub Core

    retired


    Keywords
    Systems Biology
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    Projects (0)

      Johann DRÉO


      As a senior research engineer, I have explored many corners of computer science and artificial intelligence. I can most notably help you on the following topics. Skills Decision support systems Boxes and arrows design and implementation of decision-aid software (web-based as well as native interfaces and backends), visualization and diagrams (how to summarize complex data/concepts in a visual way), integration of third-party modules (how to design API to use external services, how to integrate software that does not really want to be integrated). Automated decision A black-box with a black-box inside score function modelling (how to design a metric defining a quality for a solution to a decision problem, while maintaining good mathematical properties), optimization problem modelling (how to design a formal model of a decision problem to be automatically solved by a computer), solving automated configuration problems (how to set parameters of a complex system so as to maximize its performances), Scientific computing Lego blocks and arrows efficient algorithmics (how to cope with combinatorial explosion or curse of dimension when implementing complex algorithms), highly modular software architectures (how to structure your code to allow efficient —and automated— exploration of your ideas), modern C++ (how to program with C++ using —almost— the same concepts than in Python), shell scripting (how to use the existing Unix tools to —very— efficiently automatize any task). Artificial Intelligence search heuristics, metaheuristics or evolutionary computation (how to solve hard optimization problems), design of experiments for randomized algorithmics (how to design experiments involving modern AI, using rigorous statistics), automated planning (how to compute shortest paths, and more generally optimize sequences of actions), semantic graph mining (how to find patterns in an ontology).


      Keywords
      AlgorithmicsData Visualization
      Organisms
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      Projects (0)

        Related projects (31)

        Mise a disposition d'un(e) bioinformaticien(ne) du hub pour les analyses bioinformatiques du transcriptome et de l epigenome

        La PF Transcriptome et Epigenome développe des projets de séquençage à haut débit (collaboration et service) avec des équipes du Campus. Ceux-ci couvrent l'ensemble des thématiques du campus ainsi qu'une large gamme d'organismes (des virus aux mammifères). La plate-forme exerce des activités de biologie humide (construction des librairies et séquençage) et de biologie sèche (analyse bioinformatiques et statistiques). La personne mise a disposition interagira étroitement avec les autres bioinformaticiens du pôle BioMics et du Hub. Ses activités concerneront notamment: - La participation à la conception et à la mise en place des projets avec les équipes demandeuses, la prise en charge des analyses et le reporting aux utilisateurs - La mise en place d'un workflow d'analyse bioinformatique des données de transcriptome /épigénome en étroite collaboration avec le C3BI, la DSI et les autres bioinformaticiens du pole. Ce workflow permettra le contrôle qualité des données, leur prétraitement, le mapping des séquences sur les génomes/transcriptomes de réference, et le comptage des reads pour les différents éléments de l'annotation - L'adaptation du workflow d'analyse aux questions biologiques et aux organismes étudiés dans le cadre des activités de la PF - L'activité de veille technologique et bibliographique (test et validation de nouveaux outils d'analyse, updates d'outils existants...) - La mise en place et le développement d'outils d'analyse adaptés aux futurs projets de la PF: single cell RNAseq, métatranscriptome, ChIPseq, analyse des isoformes de splicing.. Ceci se fera notamment via la réalisation d'analyses dédiées avec certains utilisateurs. Les outils mis en place et validés dans ce cadre seront ensuite utilisés pour l'ensemble des projets. - L'activité de communication et de formation (participation aux réunions du consortium France Génomique,formation permanente à l' Institut Pasteur… - la participation a d autres projets du Pole BioMics (selon disponibilité) Bernd Jagla, qui était le bioinformaticien de la plateforme a rejoint le Hub au 1er janvier 2016. Rachel Legendre est mise a disposition depuis le 2 novembre 2015 et remplace Bernd Jagla. Je souhaite que Rachel Legendre soit mise à disposition de la plateforme pour une durée d'au moins 2 ans.



        Project status : Closed

        Biomarqueurs d’identification précoce du sepsis aux urgences (BIPS)

        Rationnel. Le mode de présentation clinique du sepsis est très polymorphe. Chez les patients septiques consultants dans les services des urgences, la présence d’une hyperthermie ou d’autres critères du syndrome de réponse inflammatoire systémique (SIRS) n’est pas suffisante pour aider au diagnostic de sepsis. De nombreux efforts de recherche ont abouti à la proposition d’innombrables biomarqueurs de sepsis essentiellement étudiés en soins intensifs. Même si certains, comme la procalcitonine (PCT) ont atteint un relativement bon degré de prédiction aux urgences, leur usage en routine demeure controversé. Compte tenu de la physiopathologie complexe du sepsis, une approche combinatoire pourrait permettre d’atteindre des performances difficilement envisageables avec un biomarqueur seul. Objectif primaire. Etudier les performances statistiques d’un panel de biomarqueurs d’intérêt, individuellement et en association, pour le diagnostic de sepsis aux urgences. Objectifs secondaires. Etudier les performances statistiques d’un panel de biomarqueurs d’intérêt, individuellement et en association, pour le diagnostic d’état septique grave (sepsis sévère et choc septique) et la stratification du risque (prédiction de l’admission en soins intensifs et/ou du décès). Type d’étude. Etude de cohorte monocentrique prospective non-interventionnelle Patients et critères d’inclusion. 300 patients consultant dans le service des urgences ayant une suspicion de sepsis + 30 sujets sains. Critères de non inclusion. Patient mineur de moins de 18 ans, femme enceinte, conditions de vie rendant impossible le suivi à 28 jours, refus de participer à l’étude. Mesures. Pour chaque patient, lors du bilan sanguin initial, prélèvement de 3 tubes pour le dosage a posteriori d’un panel de biomarqueurs d’intérêt explorant les différentes voies biologiques activées au cours du sepsis.  



        Project status : Closed

        MOODel: Modeling Mood Disorders

        Mood disorders such as bipolar and major depressive illnesses are among the most severe psychiatric disorders. They have high prevalence and chronic course, and are associated with significant mental and somatic comorbidities and high personal and societal costs (lost productivity and increased medical expenses). Patients with bipolar disorder (BD), for example, exhibit a reduced lifespan compared with the general population, a finding that cannot only be explained by high suicide risk, reduced access to medical care and lifestyle factors. However, the pathophysiological mechanisms of BD are poorly understood, and patients often have incomplete treatment response. Advanced mathematical approaches such as machine learning techniques are increasingly being used to generate predictions based on complex data, and it has been successfully used to detect a number of clinical outcomes and to predict behaviours. In combination with mobile technologies (e.g. smartphones, wearables) to collect behavioural, physiological and environmental data, these big data predictive approaches may provide a much richer and deeper understanding of phenomenology and pathophysiological mechanisms of mood and bipolar disorders. By taking advantage of the high-standard bioinformatics expertise offered by the C3BI, this multidisciplinary, collaborative project aims to explore how clinical and biological factors, may contribute for better characterizing BD patients as well as to identify predictors of treatment response in BD. Our project also aims to explore how daily behavioural and physiological parameters may influence mood and behaviour in individuals at-risk or suffering from mood disorders.



        Project status : Closed

        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

        Providing correlationPlus software to the scientific community for analysis of dynamical correlations in biological macromolecules

        Molecular dynamics simulations and elastic network models are two widely used computational methods for investigation of dynamics of biological macromolecules. These methods can reveal dynamical correlations between residues, nucleotides, domains and chains of biological macromolecules. Even though analyses of these correlations are employed frequently, there is not an application and API that can facilitate the analysis and the visualization of them. A coherent API/app can accelerate the analysis process and reveal details of allosteric interactions. We developed a Python package called correlationPlus that can facilitate and accelerate the dynamical correlation analyses. The package contains both an API and a command line interface. It analyzes raw dynamical correlation maps and plots 2D heatmaps. It can extract the correlation map of individual chains automatically. The correlations can be projected onto PDB structures with correlationPlus and they can be visualized by the popular molecular visualization software VMD. Several studies showed that graph theoretical analysis of dynamical correlations can reveal active sites and domains within proteins. correlationPlus provides a purely Python framework to calculate several graph theoretical centrality measures such as degree, betweenness, closeness, current flow closeness, and current flow betweenness etc. In addition to 2D figures of the centralities, the centrality measure in question can also be projected onto the protein structure with correlationPlus for 3D inspection by VMD. To make correlationPlus app and API available to the scientific community, we need to package and make it distributable. As in many scientific software, correlationPlus also depend on many excellent libraries such as numpy, matplotlib, prody etc. Installation of correlationPlus with pip and/or conda can help the users to install correlationPlus by satisfying the requirements automatically. In this way, the end-users can analyze dynamical correlations rapidly. Unfortunately, we do not have any expertise in the packaging and distribution of Python packages. As a result, we need technical expertise of C3BI for packaging and making correlationPlus distributable to the scientific community.



        Project status : Closed

        Phages - bacteria interactions network of the healthy human gut



        Project status : Closed

        Identification of ASD markers using HD-EEG



        Project status : In Progress

        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