• Digital World and Robotics

Lille bioinformatics platform (Bilille)

Platform

Description

Bilille is the Lille bioinformatics platform. We support research units and platforms in biology and health in their activities by providing bioinformatics or biostatistical support. Bilille’s scientific scope includes in particular: omics data analysis, sequence annotation, phylogeny, systems biology, structural bioinformatics, integrative biology, high content screening data analysis and image data analysis. The platform's cross-disciplinary and diversified expertise in the analysis of data from the fields of biology, environment and health research enables it to offer a wide range of local services, from consulting to support in your projects, whether you are a beginner or an experienced researcher. We are open to all collaborations, academic or industrial.

Contacts

  • Guillemette Marot
    Scientific manager
  • Pierre Pericard
    Technical manager
  • Jimmy Vandel
    Technical manager

Informations

Bâtiment ESPRIT, Avenue Paul Langevin
Campus Cité scientifique, Université de Lille
59650 VILLENEUVE D'ASCQ

https://wikis.univ-lille.fr/bilille/

Lille bioinformatics platform

Chiffres clés

• more than 400 users since 2016
• ~ 20 projects supported per year
• ~ 30 days of training per year
• 2-3 scientific days per year

Effectif

Effectif total : 9

Expertises

Skills

• Omics data analysis (genomics, transcriptomics, proteomics, metagenomics, epigenomics, ...)
• Imaging data analysis
• Development of analysis pipelines and databases
• Integrative biology
• Annotation of genes, genomes and proteins
• Phylogeny
• Systems biology
• Structural bioinformatics
• Analysis of high content screening data
• Development of bioinformatics and biostatistics tools

Example(s) of projects

• mirKwood: complete pipeline for the identification and annotation of microRNAs in plant genomes from small-RNA-seq sequencing data 🡭
• Viscorvar: R package for visualizing multi-block data integration results 🡭
• Norine: software platform for the analysis of non-ribosomal peptides 🡭
• Assembly and annotation of metatranscriptomic data of flax retting in the field
• Integration of data (transcriptomics, metabolomics, metagenomics, cytometry, clinical) by statistical approaches in the study of the role of cytokines in metabolic, intestinal and pulmonary alterations

Collaborations/Partners/Scientific clients

Institut Français de Bioinformatique, Institut National du Cancer (INCa), Laboratoire MAP UMR5240, Plateforme "Exploration du Métabolisme" INRAE Clermont-Ferrand

Collaborations/Partners/Private Clients

Copalis, ANSES

Services offers

Applications sectors

  • Science / Research

Services provided

• Analysis of biological data (sequencing data, evolution modeling, proteomics, annotation of genes, proteins and genomes, data screening, cytometry, structural bioinformatics, glycobiology)
• Development of software tools, pipelines or databases
• Provision of software resources
• Provision of high-performance computing resources
• Setting up collaborative projects requiring expertise in bioinformatics and/or biostatistics

Training offers

• Training in bioinformatics tools and approaches (databases, blast, annotation, alignment, phylogeny)
• Training in high-throughput sequencing data analysis (DNA sequencing, RNA-seq, Variants, Metagenomics, ChIP-seq)
• Training in data analysis with R and Bioconductor

Consulting services

We provide consulting services related to all our areas of expertise.

Equipments

We possess a Cloud: 360 CPU cores, 3 Tb RAM, 140 Tb storage, including about ⅓ integrated into the Biosphere national federation. Available to the community for data analysis projects.

See the detailed list of equipment: https://wikis.univ-lille.fr/bilille/calcul

Ecosystem

Affiliated institutions / organisations

CHU de Lille
Inserm
CNRS

Partner institution(s)

INRIA

Unit(s) of attachment

Groups/Networks/Federations

Labellisations

Regional strategic areas of activity

  • Digital World and Robotics
    • Artificial intelligence, image processing, data science