Pasteur HUB

The EDAM Browser is a client-side web-based visualization javascript widget of the EDAM ontology.
The EDAM Browser provides users a simple and performant interface to explore EDAM when annotating or searching for bioinformatics resources.
Its goals are to help describing bio-related resources and service with EDAM, and to facilitate and foster community contributions to EDAM.

A package that provides tools for efficient FASTQ files manipulation.

Program to model and detect macromolecular systems, genetic pathways... in protein datasets. In prokaryotes, these systems have often evolutionarily conserved properties: they are made of conserved components, and are encoded in compact loci (conserved genetic architecture). The user models these systems to reflect these conserved features, and to allow their efficient detection.

This tool allows users to perform an automated workflow to analyze, validate and visualize large HDX-MS datasets. The input file is the output of DynamX software from Waters. Output files provide a plot of the data, the fitted model for each peptide, a plot of the calculated p -values, and a global visualization of the experiment. User could also obtain an overview of all peptides on the 3D structure.

R package dedicated to the differential analysis of RNA-seq data. It provides tools to generate descriptive and diagnostic graphs, to run the differential analysis with one of the well known DESeq2 or edgeR packages and to export the results into easily readable tab-delimited files. It also facilitates the generation of a HTML report which displays all the figures produced, explains the statistical methods and gives the results of the differential analysis.

SHiny application for Metagenomic ANalysis including the normalization, the differential analysis and mutiple visualization. It is based on DESeq2 R package [Anders and Huber 2010] for the analysis of metagenomic data, as suggested in [McMurdie and Holmes 2014, Jonsson2016]. It robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [Love 2014].

Comparative and interactive viewer for microbial genomes, designed to run as either a web-based tool (Flash technology) or a desktop application (AIR environment). The basis of the program is a generic genome browser with sub-maps holding information about genomic objects. The software is characterized by the presentation of syntenic organisations of microbial genomes and the visualization of polymorphism data along these genomes; these features are accessible to the user in an integrated way.

The Viral Host Range database represents a unique resource for the community to rapidly find, document analyze and disseminate data related to the range of hosts that a virus can infect. Over the years, countless host range experiments have been performed in many laboratories. However, these data are not readily available to the community and are therefore underexploited.

The VHRdb is an online resource that centralizes experimental data related to the host range of viruses. While it originates from bacteriophages and bacteria interaction studies, its design is compatible with viruses infecting all living forms. Users can browse publicly available data to find which host is infected by a virus, and vice versa. Users can also upload their own data while keeping it private or making it public, analyze results across independent sets of data, generate and visualize outputs. Data implemented in the VHRdb are linked to users and, if available, to publications and sequence identifiers.

• Biologie
• Biomédical

Le centre de bioinformatique et de biostatistique est la partie service du département de biologie informatique. L’équipe du Hub comprend 50 experts en biostatistique et en bioinformatique. Créé en 2015, le C3BI comprend cinq unités de recherche en biologie computationnelle et le Hub de bioinformatique et biostatistique. La mission du centre est de développer la recherche méthodologique en bioinformatique et biostatistique, de donner une visibilité internationale à l'Institut Pasteur dans ce domaine, d'offrir un soutien aux unités de recherche expérimentale, et de développer les compétences informatiques et analytiques du campus. Les activités de la plateforme comprennent la participation à des projets de recherche et d'analyse, des missions sur le terrain au sein des unités et des plateformes du campus, des sessions de formation et d'enseignement ouvertes à nos partenaires, et fournissent un certain nombre de ressources à la communauté nationale et internationale. L’équipe du Hub et l’ensemble du département ont une longue expérience dans le développement de sites web (par exemple NGPhylogeny.fr), les calculs intensifs et la gestion des données de santé.

• Methodology
• QTL Localization
• Biostatistics
• Metagenomics
• Expression
• Small and long non-coding RNAs
• GPU
• Quantification
• E-learning
• Tiling
• Sequence Algorithm
• DNA biochips
• RNA biochips
• Statistical differential analysis
• Evolution and Phylogeny
• Molecular evolution
• Methylation profiles
• Machine learning
• Chromatin accessibility
• Chromosome conformation analysis
• Bioimaging
• Visualization
• Biological network inference and analysis
• Selection Detection
• Assembly of genomes and transcriptomes
• Read alignment on genomes
• Supertrees and Reconciliations
• Statistical Tests
• Regression
• Dimension reduction
• Gene expression regulation analysis
• Image analysis
• Information retrieval
• Descriptive statistics
• Multivariate analyses
• Gene expression differential analysis
• Web portals
• metatranscriptomics
• Chip-Seq
• Panels (amplicons, captures)
• Exomes
• Sequence analysis
• Variant analysis
• proteomics
• Interfaces
• Systems Biology
• Interoperability
• Metabolic network analysis
• Genome analysis
• Structural and functional annotation of genomes
• Statistical Genetics
• Quantitative proteomics
• Complete genomes
• Transcript and transcript variant analysis
• Transcriptomics (RNA-seq)
• Genomics (DNA-seq)
• Functional and regulatory pathways comparison
• Genomics (Chips)
• Cluster
• Genomes comparison
• Comparative genomics
• Computing Environments
• Data Integration
• Data management and transfer
• NGS Sequencing Data Analysis
• Homology/orthology prediction
• Structural Bioinformatics
• Phylogenomics
• Données
• Mapping
• Sequence annotation
• Pattern matching
• Multiple sequence alignment
• Tool integration
• Workflow development
• Parallelization
• Databases and information systems

Description : La formation EBAII IFB Aviesan de niveau 1 propose une expérience d'apprentissage intensive conçue pour les biologistes, qu'ils soient ingénieurs, doctorants, chercheurs, enseignants-chercheurs ou praticiens, qui sont confrontés à l'analyse de données NGS (Next-Generation Sequencing) mais qui ne disposent pas encore des compétences bioinformatiques nécessaires, ou qui cherchent à renforcer leurs compétences existantes.

Contenu : Cette formation est structurée autour d'une combinaison de sessions théoriques et d'ateliers pratiques. Les participants auront l'occasion d'explorer diverses thématiques, notamment le traitement de données de variants, ChIP-Seq, Bulk RNA-Seq, et Single-Cell RNA-Seq. De plus, ils recevront une introduction aux technologies "long reads".

Objectifs généraux:
Acquérir une compréhension approfondie des concepts liés à l'analyse de données NGS.
Maîtriser les outils informatiques nécessaires pour effectuer ces analyses.
Interpréter les résultats des analyses de données NGS.