Thibaut GUIRIMAND

Edito

Welcome on my website!

You can find here the ideas and projects I'm working on. You can either get information about my skills and experience.

Presently, I'm looking for job opportunities on different topics like Data Mining, graph theory or algorithms for natural speech recognition. If you have an opportunity please contact me at [name]@[surname].eu .

Enjoy and don't play pong for too long!

Thibaut

PS: I'm really sorry for your eyes but I love this website green color  :-p

2021-11-16

Want to play pong?

This week end was addapted to learn about the HTML5 canvas tag. So here is my pong ^^

If you want to use it in your website, follow this link.



2016-01-24

A new design.

The website has a new very green design !

2015-04-12

Research themes and Interest

Bioinformatics Algorithmic & Development Data Mining Graph Theory Omics

Curriculum Vitae

Work Experience

  • Jan 2020 - Actual
    Data Scientist at spartoo.com Grenoble, France Marketing and Fraud prediction models development. Industrialization processes conception applied to data science problematics.
  • Mar 2018 - Jan 2020
    Java Engineer and Data Scientist at Sopra-Steria Grenoble, France Java EE developper for Telecom and Public Services Client. Statistical and predictive model development, proof of concept realization to explore and valorize our client's data.
  • Nov 2015 - Aug 2017
    Database Engineer at INRA Jouy-en-Josas, France Database conception for a cheese shotgun metagenome analysis software. Project specifications, web interface conception and users training. MICALIS Unit, FME team
  • Jan 2015 - Jun 2015
    Intern in the Sentinelles Network Paris, France Conception of a new data exchange format for public health using web semantics technologies and the Data Cube Vocabulary standard. tutor : Sc.D. Clément Turbelin
  • Apr 2014 - Jul 2014
    Intern at Pôle Rhône-Alpes de Bioinformatique Villeurbanne, France Development of the VirHostNet database web interface, to highlight graph metric about virus-host protein interactions and make the new database release publishable and maintainable. tutor : Sc.D. Vincent Navratil
  • Feb 2013 - Jul 2013
    Intern at Pôle Rhône-Alpes de Bioinformatique Villeurbanne, France Web design of the VirHostNet database interface to Integrate the Cytoscape Web technology for vizualisation of protein interaction. tutor : Sc.D. Vincent Navratil
  • Jul 2012 - Aug 2012
    Intern at Novadiscovery Lyon, France Analysis and referencing of biomathematics models from the scientific literature. tutor : Sc.D. Gustavo Olivera

Education

  • 2013 - 2015
    Master in Bioinformatics University Denis Diderot Paris, France
  • 2010 - 2013
    Degree of computer modeling of living University Claude Bernard Lyon 1 Villeurbanne, France
  • 2008 - 2010
    First year of Pharmacy study University Claude Bernard Lyon 1 Lyon, France
  • 2005 - 2008
    Scientific Baccalauréat Lycée du Granier La Ravoire, France

Diplomas

  • 2013
    Degree of computer modeling of living University Claude Bernard Lyon 1 Villeurbanne, France
  • 2012
    C2i niveau University Claude Bernard Lyon 1 Villeurbanne, France
  • 2008
    Scientific Baccalauréat Lycée du Granier La Ravoire, France
  • Attestation Européenne de Formation aux Premiers Secours French Red Cross Chambéry, France

Computer Skills

Python HTML5/CSS3 LaTeX SQL C/C++ Java R Julia PHP RDF UML

Interests and Activities

SkiingMountain BikeBadmintonClimbingDrawing

Research Projects

Empty.

Personal Projects

Empty.

Some short scripts

sPy

Create a new executable Python script :

       #!/usr/bin/env bash
echo '#!/usr/bin/env python' > $1
chmod a+x $1
$EDITOR $1
       

You can use it by writting : sPy your_new_script

sSh

Create a new executable Bash script :

       #!/usr/bin/env bash
echo '#!/usr/bin/env bash' > $1
chmod a+x $1
$EDITOR $1
       

You can use it by writting : sPy your_new_script

VirHostNet 2.0: surfing on the web of virus/host molecular interactions data

Authors

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Format

Article

Abstract

VirHostNet release 2.0 (http://virhostnet.prabi.fr) is a knowledgebase dedicated to the network-based exploration of virus–host protein–protein interactions. Since the previous VirhostNet release (2009), a second run of manual curation was performed to annotate the new torrent of high-throughput protein–protein interactions data from the literature. This resource is shared publicly, in PSI-MI TAB 2.5 format, using a PSICQUIC web service. The new interface of VirHostNet 2.0 is based on Cytoscape web library and provides a user-friendly access to the most complete and accurate resource of virus–virus and virus–host protein–protein interactions as well as their projection onto their corresponding host cell protein interaction networks. We hope that the VirHostNet 2.0 system will facilitate systems biology and gene-centered analysis of infectious diseases and will help to identify new molecular targets for antiviral drugs design. This resource will also continue to help worldwide scientists to improve our knowledge on molecular mechanisms involved in the antiviral response mediated by the cell and in the viral strategies selected by viruses to hijack the host immune system.

Full text

Cheese ecosystems insights with shotgun metagenomics and a metadata extended genomics database.

Authors

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Format

Poster

Abstract

The manufacturing process of cheeses, as for most fermented food, involves a complex flora, which is composed of bacteria, yeast and filamentous fungi. They can be directly inoculated as starter culture or develop from the food-chain environment (raw milk, cheese factory...). Therefore the exact composition of most cheeses is not completely known.

Further understandings of cheeses ecosystems and control of cheese quality both need a better characterization of the cheese flora with a precise taxonomic identification. The FoodMicrobiome-Transfert project aims to address these challenges.

In the framework of this project, we are developing a tool to facilitate metagenomics analysis. This tool is composed of read alignment wrapper tool, a database and a web interface to run analysis.

GeDI : an in-house metagenomics analysis tool

Shotgun metagenomics sequencing data brings information about the studied ecosystem, but also yields noise signal. Hence retrieving the link between sequence and organism is not trivial and require different strategies.

Several current metagenomics tools are based on a set of gene markers, or on the k-mer composition of the reads, but few are able to identify species up to the strain level. We are developing an in-house software to wrap read alignments on reference genomes and extract information from these processes. It relies on the intersection between features (CDS) and alignments data (BAM) to infer species presence or absence.

A web application and a database to exploit GeDI possibilities

The application will allow the users to submit metagenomes and personal genomes. They will be able to choose a list of genomes from our public database and from their personal genome library. They will finally be able to execute GeDI to analyze their metagenome data. The database, currently in development, will store (i) genomics data from food-related microorganisms that will be used for metagenomics data analysis, (ii) metadata associated with the ecology of these microorganisms and (iii) metagenomics analysis results. The database genomics part will be enriched with expert annotations, with a focus on genes of technological interest. The application will permit to visualize and compare analysis results and cheese environments metadata.

Technical specificities

The tools will be hosted on the Migale platform. The GeDI software will be run transparently on the Migale Galaxy portal using our specific web interface. The Python 3 Django web communicates with Galaxy using the bioblend library and allow us to easily manage datasets and outputs. Information are exchanged through bioinformatics standard files (GFF, BAM, etc.), thus easing the use or the export to others tools.

Congress

JOBIM 2016

Poster

Food Microbiome-Transfert, a database to characterize cheese ecosystems.

Authors

, , , , ,

Format

Poster

Abstract

Congress

INRA Bioinformatics days 2016

Poster

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