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AuBi

Adress
CBRV Facultés Médecine & Pharmacie 28 Place Henri Dunant 63001 Clermont-Ferrand
INRA Theix 63122 Saint-Genes-Champanelle
Structure(s)
INRA
Unit:
UMR 454 MEDIS INRA-Université Clermont Auvergne
[field_pole_regional_de_rattachem]
Website
AuBI - Université de Clermont Auvergne (UCA)
Scientific leader(s)
Technical leader(s)
Certificat(s)
Not documented
Team
Infrastructure
Hébergée
Effective storage
520.00 To
Cluster: cores number
1 088 cores
Data collections number
4
CPU/hours a year
4 700 000 H / an
Bioinformatic tools number
44
Users number (last year)
143
Servers description

Ressources mutualisées du Mésocentre Clermont Auvergne.

Cluster de calcul avec SLURM, stockage distribuée avec CEPH, plateforme d'hébergement de services avec VMWARE.

Projets 2017 : calculateur haute performance à mémoire partagée, Cloud IaaS de production Openstack.

Hébergement dans le datacenter de l'Université Clermont Auvergne.


Access conditions

Accès créés à la demande pour les chercheurs du site, sur projet pour les autres accès.

Il n’y a pas de ressources spécifiquement réservées à la PF pour l’instant.

 
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Quotes:
2
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dbWFA

Description

Open-access database relating the Full-length cDNA sequences from TriFLDB, the transcripts of the wheat set UniGene (builds # 55,58, 59 and 60; UniGene) and the wheat Transcription Factor DataBase (wDBTF) that have been used to design a wheat NimbleGen 40k UniGene microarray (ArrayExpress: ref. A-MEXP-1928) to Arabidopsis thaliana (TAIR10), Oryza sativa (rice plantbiology MSU) and Zea mays (MaizeGDB) databases through BLAST results. Transfert vers le CRRI.

 

Publications :
    Vincent J, Dai ZW, Ravel C, Choulet F, Mouzeyar S, Bouzidi MF, Agier M, Martre P. (2013)  dbWFA: a web-based database for functional annotation of Triticum aestivum transcripts. Databases. doi: 10.1093/database/bat014

 

Access conditions

Gratuit sur https://urgi.versailles.inra.fr/dbWFA/
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ECOD

Description

Database which contains 15364 probe sequences that target Encephalitozoon cuniculi genome. For each CDS, 3 oligonucleotides where computed using OligoArray software and GoArrays software. It is also possible to browse Encephalitozoon cuniculi genome.

 

Access conditions

Gratuit sur http://g2im.u-clermont1.fr/serimour/ecod/index.html
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FatAndMuscleDB

Description

Genomics on muscle and adipose tissue growth has generated huge amount of data which are available in journals and in databases. Unfortunately these data are scattered on the Internet in a heterogeneous format. Thus, it is difficult to exploit them efficiently. We hypothesise that these data can allow identifying genes or proteins involved in adipose and muscle tissues development contributing to body or muscle composition, two key criteria of carcass and meat quality. Currently, Fat&MuscleDB contains genomic expression data and differential abundance data which can be queried, visualised, and downloaded in different ways: the data visualisation of each reference, the search of transcripts or proteins in references, and the data aggregation based on criteria of adipose and muscle growth.

Access conditions

Gratuit sur https://umrh-bioinfo.clermont.inrae.fr/FatAndMuscleDB/index.php
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30 an
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HuGChip

Description

Phylogenetic microarray designed to study the human gut microbiota at family level.  This database contains the whole probe set.

 

Publications:
     Tottey W., Denonfoux J., Jaziri F., Parisot N., Missaoui M., Hill D.R.C., Borrel G., Peyretaillade E., Alric M., Harris H.M.B., Jeffery I.B., Claesson M.J., O'Toole P.W., Peyret P., Brugère J.-F. (2013). The Human Gut Chip “HuGChip”, an Explorative Phylogenetic Microarray for Determining Gut Microbiome Diversity at Family Level. PLoS One. 8, e62544. DOI: 10.1371/journal.pone.0062544

      Feria-Gervasio D., Tottey W., Gaci N., Alric M., Cardot M., Peyret P., Martin J.-F., Pujos E., Sébédio J.-L., Brugère J.-F.. Three-stage continuous culture system with a self-generated anaerobia to study the regionalized metabolism of the human gut microbiota. J. Microbiological Meth. 2014, Vol. 96, pp 111-118. DOI: 10.1016/j.mimet.2013.11.015

Access conditions

Gratuit sur http://g2im.u-clermont1.fr/HuGChip/
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PhROGs

Description

Cette base de données contient 38,880 PhROGs (groupes de protéines orthologues) contenant 868,340 protéines provenant de génomes complets de virus infectant les  bacteries ou archées (Roux et al., 2015).
Ce site web donne accès aux :

  • génomes des virus procaryotiques et de sélectionner taxonomie, liste de protéines, cartes génomiques, etc...
  • tous les PhROGs et sélectionner annotations, liste de protéines, alignement multiple, comparer les résultats au données Pfam, Uniprot, KEGG, etc...
Access conditions

Gratuit sur https://phrogs.lmge.uca.fr/
No website documented
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Unique visits:
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Quotes:
3
Latest update:
30-01-2014

PhylOPDb

Description

Online resource for a comprehensive phylogenetic oligonucleotide probe database. PhylOPDb provides a convivial and easy-to-use web interface to browse both regular and explorative 16S rRNA-targeted probes.

Two high-throughput probe design software, PhylGrid (Jaziri et al., 2011; Jaziri et al., 2014) and KASpOD (Parisot et al., 2012), we used to select both regular and explorative 16S rRNA gene-targeted oligonucleotide probes. Such probe set or subset could be use to globally monitor known and unknown prokaryotic communities through various techniques including DNA microarrays, Polymerase Chain Reaction (PCR), Fluorescent In Situ Hybridisation (FISH), targeted gene capture or in silico rapid sequence identification.

 

Publications :
    Jaziri, F., Parisot, N., Abid, A., Denonfoux, J., Ribière, C., Gasc, C., Boucher, D., Brugère, J.-F., Mahul, A., Hill, D.R.C., Peyretaillade, E. and Peyret, P. (2013) PhylODb: a 16S rRNA oligonucleotide probe database for prokaryotic identification, Oxford Database.

Access conditions

Gratuit sur: http://g2im.u-clermont1.fr/phylopdb/
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ActivCollector

Description

Estimation tools design of energy expenditure and energy intake.

 

Access conditions

Gratuit
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Ant-Motifs

Description

Motifs extraction and supervised classification for proteins structure.

Publications :

R. Saidi, M. Maddouri, and E.M. Nguifo (2010) Protein sequences classification by means offeature extraction with substitution matrices. BMC bioinformatics, 11(1): 175. doi:10.1186/1471-2105-11-175

R. Saidi, W. Dhifli, M. Maddouri, and E.M. Nguifo. (2019) Efficiently Mining Recurrent Substructures from Protein Three-Dimensional Structure Graphs. J. Comput. Biol., 26 (6), 561-571. doi:10.1089/cmb.2018.0171

 

Access conditions

Gratuit sur http://www.isima.fr/~mephu/FILES/AntMotif/
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Annual visits:
72 000 an
Unique visits:
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Quotes:
3
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DroPNet

Description

Drosophila Protein Network allows the generation and analysis of protein-protein interaction (PPI) networks. This platform will help integrating user experimental data with various available PPI databases.

Publication :
Y. Renaud, A. Baillif, J-B. Perez, M. Agier, E. Mephu Nguifo, V. Mirouse (2012) DroPNet: a web portal for integrated analysis of Drosophila protein-protein interaction networks.  Nucleic Acids Research, 40(Web Server issue):W134-9, Oxford. doi:10.1093/nar/gks434

 

Access conditions

Gratuit sur http://dropnet.isima.fr/site/
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Quotes:
3
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GoArrays

Description

Microarray probe design application. It enables the design of specific probes of each gene in an entire genome, with an original approach. The use of specific microarray technology requires a very detailed attention for the design of specific probes spotted on the solid phase. These problems are far from being commonplace since they refer to complex physicochemical constraints. We propose a new approach to design oligonucleotides which combines good specificity with a potentially high sensitivity. This approach is original in the biological point of view as far as in the algorithmic point of view, and is particularly adapted when dealing with a complex target mixture (where it’s difficult to find specific sequences fo all genes).

    Publication :
    Rimour, S., D. Hill, C. Militon, and P. Peyret (2005) GoArrays: highly dynamic and efficient microarray probe design. Bioinformatics (Oxford, England) 21:1094-1103. doi:10.1093/bioinformatics/bti112

 

Access conditions

Gratuit sur http://g2im.u-clermont1.fr/serimour/goarrays.html
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Unique visits:
55 an
Quotes:
6
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HiSpOD

Description

Software dedicated for the microbial ecology and environmental studies. The software use individual nucleic sequences or consensus sequences produced by multiple alignments to design degenerate probes in order to target gene families covering many exhaustive formatted database dedicated to microbial ecology containing about 10 million coding sequences (CDS) and their putative 5’ and 3’ untranslated regions (UTR). Potential cross-hybridizations identified by the program are clustered and results are organized in order to simplifyuser interpretation.

Publications :

Dugat-Bony E., Missaoui M., Peyretaillade E. , Biderre-Petit C. , Bouzid O., Gouinaud C. , Hill D. , and Peyret P. (2011) HiSpOD: probe design for functional DNA microarrays. Bioinformatics (Oxford, England) 27:641-648. doi:10.1093/bioinformatics/btq712

Parisot N., Peyretaillade E., Dugat-Bony E., Denonfoux J., Mahul A., and Peyret P. (2016) Probe Design Strategies for Oligonucleotide Microarrays. Methods in Molecular Biology, 1368: 67-82. doi: 10.1007/978-1-4939-3136-1_6

Access conditions

Gratuit sur http://g2im.u-clermont1.fr/hispod/index.php
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Annual visits:
92 an
Unique visits:
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Quotes:
5
Downloads:
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KASpOD

Description

Program for designing signature sequences for various applications including in phylogenetic or functional microarray experiments.

 

Publication:

Parisot, N., J. Denonfoux, E. Dugat-Bony, P. Peyret, and E. Peyretaillade (2012) KASpOD--a web service for highly specific and explorative oligonucleotide design. Bioinformatics (Oxford, England) 28:3161-3162.doi:10.1093/bioinformatics/bts597

Access conditions

Gratuit sur http://g2im.u-clermont1.fr/kaspod/
No website documented
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Quotes:
2
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MetabolicDesign

Description

Algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes. (téléchargeable).

    Publication :
    Terrat, S., E. Peyretaillade, O. Goncalves, E. Dugat-Bony, F. Gravelat, A. Mone, C. Biderre-Petit, D. Boucher, J. Troquet, and P. Peyret (2010) Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development. BMC Bioinformatics 11:478.
 

Access conditions

Gratuit
No website documented
Annual visits:
Not documented
Unique visits:
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Quotes:
3
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MetaExploArrays

Description

Large scale oligonucleotide probe design software for explorative DNA microarrays. It allows selecting probes for an individual specific nucleic acid sequence or a group of sequences. It used a parallel approach to simultaneous design of thousands of sensitive, specific, isothermal and explorative

 

Publication :
    Jaziri, F., Parisot, N., Denonfoux, J., Dugat-Bony, E., Peyretaillade, E., Peyret, P. and Hill, DRC (2012) MetaExploArrays: a large-scale oligonucleotide probe design software for explorative DNA microarrays. Proceedings of the IEEE Thirteenth International Conference on Parallel and Distributed Computing, Applications and Technologies PDCAT2012, IEEE, Beijing, China, 2012, ISBN: 978-0-7695-4879-1, 660-667.

Access conditions

Gratuit
No website documented
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Unique visits:
600 an
Quotes:
32
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Metavir

Description

Web server for the analysis of viral metagenomes. Results from a variety of analyses realized on public viromes can be visualised. Users can also upload their own data in a private mode to be analysed. Recently Metavir was updated to allow for the analysis of assembled viromes.

    Publications :
    Roux, S., M. Faubladier, A. Mahul, N. Paulhe, A. Bernard, D. Debroas, and F. Enault (2011) Metavir: a web server dedicated to virome analysis. Bioinformatics (Oxford, England) 27:3074-3075.
    Roux, S., J. Tournayre, A. Mahul, D. Debroas, and F. Enault (2014) Metavir 2: new tools for viral metagenome comparison and assembled virome analysis. BMC bioinformatics 15:76.

Access conditions

Gratuit sur http://metavir-meb.univ-bpclermont.fr/
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MicroAnnot

Description

Pipeline dedicated to microsporidian genome annotation under Galaxy. Not already published.

 

Access conditions

Gratuit sur http://galaxy01.calcul.crri.fr/
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Annual visits:
35 an
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MIL-ALIGN

Description

Phenotype predictor of ionizing-radiation-resistant bacteria by extraction of discriminative motifs using a multiple-instance learning model.
 

 

Access conditions

Gratuit sur http://www.isima.fr/~mephu/IRR/
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Quotes:
2
Downloads:
84

Nucbase

Description

Program designed to make an exhaustive search for sequence matches and to align short sequence reads from large nucleic acid databases to genomes or input sequences.

Publication :
    Dufourt, J., P. Pouchin, P. Peyret, E. Brasset, and C. Vaury (2013) NucBase, an easy to use read mapper for small RNAs. Mobile DNA 4(1):1.doi:10.1186/1759-8753-4-1

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Gratuit sur https://grr.gred-clermont.fr/nucbase
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NucleusJ

Description

Plugin for 3D image analysis.

    - Publication :
Poulet, A., I. Arganda-Carreras, D. Legland, A. V. Probst, P. Andrey, and C. Tatout (2015) NucleusJ: an ImageJ plugin for quantifying 3D images of interphase nuclei. Bioinformatics (Oxford, England) 31(7):1144-1146. doi:10.1093/bioinformatics/btu774

Access conditions

Gratuit sur http://imagejdocu.tudor.lu/doku.php?id=plugin:stacks:nuclear_analysis_pl...

Wiki ImageJ requis.
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P-MetaStackPrt

Description

Parallel software to compute a complete backtranslation of short peptides to select probes for functional microarrays. P-MetaStackPrt uses meta-programming and a model driven engineering approach to automatically generate source codes to perform complete backtranslation on different architectures: PCs, Symmetric Multiprocessors servers, computing clusters, or a computing grid. P-MetaStackPrt is filtering the generated oligonucleotides with usual selection criteria for the design of microarray probes. It can be easily integrated in probe design software for functional microarrays.

 Publication :
    Jaziri, F., Peyretaillade, E., Peyret, P. and Hill, DRC (2014) High Performance Computing of Oligopeptides Complete Backtranslation applied to DNA microarray probe design. Concurrency and Computation: Practice and Experience, DOI: 10.1002/cpe.3412, 19p.

 

Access conditions

Gratuit
Check the website
Annual visits:
70 an
Unique visits:
40 an
Quotes:
14
Downloads:
15

PANAM

Description

PANAM  makes it possible to analyse a large dataset of 18S rRNA in a simple and rapid way. It assigns taxonomy to reads generated by next generation sequencing technologies or to near-full-length sequences, and permits to define environmental clades. A readme file text that contains instructions to set up PANAM is available in the package (Taib et al. 2013).

    Publication :
    Taib, N., J. F. Mangot, Domaizon, I., Bronner G., and Debroas D. (2013) Phylogenetic affiliation of SSU rRNA genes generated by massively parallel sequencing: new insights into the freshwater protist diversity. PloS one 8:e58950.doi:10.1371/journal.pone.0058950

 

Access conditions

Gratuit sur https://code.google.com/p/panam-phylogenetic-annotation/
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PanGeneHome

Description

PanGeneHome is a web server dedicated to the analysis of available microbial pangenomes. Several standalone tools (e.g. PGAP, PANNOTATOR, PanGP, Roary and BPGA) and web servers (e.g. Panseq, PGAT and PanWeb) dedicated to pangenome analysis have been developed recently and offer the possibility to compute pangenome analysis for genomes provided by a user. For all these tools and servers, users have to collect genomes and manage to run the tools, which implies a significant effort on the user side. To tackle this problem, we developped PanGeneHome, the only web site offering pre-computed pangenome analysis with up-to-date and large scale data. PanGeneHome provides an easy way to get a glimpse on the pangenome of a microbial group of interest, the analysis being precomputed and available for 615 taxa, covering 182 species and 49 orders. Considering the fast growing number of microbial genomes, the PanGeneHome tool will need to be updated regularly.

Publication:

Loiseau C., Hatte V., Andrieu C., Barlet L., Cologne A., De Oliveira R., Ferrato-Berberian L., Gardon H., Lauber D., Molinier M., Monnerie S., N 'Gou K., Penaud B., Pereira O., Picarle J., Septier A., Mahul A., Charvy J.-C. and Enault F. (2018) Journal of Bioinformatics, Computational and Systems Biology. arXiv:1805.05597

Access conditions

Gratuit
Check the website
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Quotes:
8
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PhylArray

Description

Program for designing oligonucleotide probes (from 16S rRNA) for use in phylogenetic microarray experiments.
    

Publication :
    Militon, C., S. Rimour, M. Missaoui, C. Biderre, V. Barra, D. Hill, A. Mone, G. Gagne, H. Meier, E. Peyretaillade, and P. Peyret (2007) PhylArray: phylogenetic probe design algorithm for microarray. Bioinformatics (Oxford, England) 23:2550-2557. doi:10.1093/bioinformatics/btm392

Access conditions

Gratuit sur http://g2im.u-clermont1.fr/serimour/phylarray/
No website documented
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Quotes:
3
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PhylGrid

Description

Distributed software for selecting regular and explorative oligonucleotide probes at large scale using a computing grid. This software can be used in various applications including in phylogenetic microarray experiments.

    Publications :
    Jaziri, F., Missaoui, M., Cipière, S., Peyret, P. and Hill, D.R.C (2011) Large Scale Parallelization Method of 16S rRNA Probe Design Algorithm on Distributed Architecture: Application to Grid Computing. Proceedings of the IEEE International Conference on Informatics and Computational Intelligence ICI2011, Bandung, Indonesia, 2011, 35-40.
    Jaziri, F., Peyretaillade, E., Missaoui, M., Parisot, N., Cipière, S., Denonfoux, J., Mahul, A., Peyret, P. and Hill, DRC (2014) Large scale explorative oligonucleotide probe selection for thousands of genetic groups on a computing grid: application to phylogenetic probe design using a curated small subunit ribosomal RNA gene database. Scientific World Journal, 2014: 9p.

Access conditions

Gratuit
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PhylInterpret

Description

Efficient parallel algorithm for DNA microarray data analysis. It uses parallel computing and the concepts of propositional logic to determine the microbial composition of a hybridized biological sample. Not already published.

 

Access conditions

Gratuit
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Prefon_Meta

Description

Functional prediction of metagenomic sequences.

 

Access conditions

Gratuit sur http://com.isima.fr/PREFON_META
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proteINSIDE

Description

ProteINSIDE is a workflow to analyse lists of protein or gene identifiers from ruminant species and gather biological information provided by functional annotations, putative secretion of proteins and proteins interactions networks. ProteINSIDE gets results from several software and databases with a single query. From a unique list, ProteINSIDE uses orthologs identifiers within well studied species (Human, Rat or Mouse) to extend analyses and biological information retrieval.

 

 Publications:

 Kaspric N., Picard B., Reichstadt M., Tournayre J., and Bonnet M. (2015) ProteINSIDE to Easily Investigate Proteomics Data from Ruminants: Application to Mine Proteome of Adipose and Muscle Tissues in Bovine Foetuses. PLoS ONE 10(5): e0128086. doi:10.1371/journal.pone.0128086

 Kaspric N., Reichstadt M., Picard B., Tournayre J., and Bonnet M. (2015) Protein Function Easily Investigated by Genomics Data Mining Using the ProteINSIDE Online Tool. Genomics and Computational Biology, [S.l.], v. 1, n. 1, p. e16, sep. 2015. ISSN 2365-7154

 

 

Access conditions

Gratuit sur https://www.proteinside.org
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RulNet

Description

Rule Inference and Network Visualization is a web-oriented platform dedicated to the inference and analysis of regulatory networks from qualitative and quantitative –omics data by means of rule discovery and statistical techniques.

 Publication :
    Vincent J, Martre P, Gouriou B, Ravel C, Dai ZW, Petit JM, Pailloux M (2015) RulNet: A Web-Oriented Platform for Regulatory Network Inference, Application to Wheat -Omics Data. Plos One 10(5) e0127127. doi:10.1371/journal.pone.0127127

Access conditions

Gratuit sur http://rulnet.isima.fr
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SeqCode

Description

Motifs extraction and supervised classification of primary protein structure.

Publication :

R. Saidi, M. Maddouri, and E.M. Nguifo (2010) Protein sequences classification by means offeature extraction with substitution matrices. BMC bioinformatics, 11(1): 175. doi:10.1186/1471-2105-11-175

Access conditions

Gratuit sur http://www.isima.fr/~mephu/FILES/SeqCod/
No website documented
Annual visits:
2 982 an
Unique visits:
1 480 an
Quotes:
10
Downloads:
Not documented

Synteny Viewer

Description

Web-oriented platform dedicated to the visualization of conserved genes/loci between species (i.e. comparative genomics or synteny) based on ancestral genomes reconstruction (i.e. paleogenomics). Users can navigate between plant (cereals, monocots, eudicots) and animal (vertebrates) genomes to transfer any structural and functional information from models to species of agricultural or medical interests. From the ongoing developments, the tools will be generic across eukaryotic phyla (plants, vertebrates, prokaryotes, protists, insects, etc.) and will target not only genome structures (gene order, sequences, etc.) but also the annotation of functions (gene ontologies, metabolic pathways, regulatory interactions, etc.). The platform will allow users to visualise conserved/specific genes either at the locus or at the gene levels in the considered genomes as well as associated gene structure, molecular evolution, expression, regulation as phenotypic and trait data, and provide access to the raw data (gene name, sequence, position, expression, methylation, repeat content context, polymorphism, phenotype, QTL, association genetics) obtained from synteny, duplication and ancestral content analyses for both plant and animal lineages. Transfert vers le CRRI.

Publication :
    Pont C, Murat F, Guizard S, Flores R, Foucrier S, Bidet Y, Quraishi UM, Alaux M, Doležel J, Fahima T, Budak H, Keller B, Salvi S, Maccaferri M, Steinbach D, Feuillet C, Quesneville H, Salse J (2013) Wheat Syntenome Unveils New Evidences of Contrasted Evolutionary Plasticity Between paleo- and Neoduplicated Subgenomes. Plant Journal. 76(6):1030-44.

 

Access conditions

Gratuit sur https://urgi.versailles.inra.fr/synteny
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Annual visits:
1 005 an
Unique visits:
89 an
Quotes:
8
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TriAnnot

Description

Web-oriented platform dedicated to the annotation of plant genome, mainly for wheat but also for maize, rice, barley and oak. The pipeline can be used to annotate full genomes through collaboration. However, on the web site, for technical reasons and parallelization purposes, 10 sequences up to 3 Mb can be submitted online at once. As it would be cumbersome to annotate several Mb or Gb of sequence this way, the online access is more adapted to small scale analyses (i.e. BAC or small BAC contigs) in which the user can submit its sequence directly on the webpage (copy/paste or download) and start the analysis with a single click. However the TriAnnot pipeline can be also used directly on command line for very large projects. The pipeline uses a queuing list for sequence submission. Therefore, the automatic structural and functional annotation process will depend of the queue length. In general, in this configuration, TriAnnot can deliver a BAC annotation in less than one hour depending of the cluster charge. For example: a default analysis of a 117 kb sequence containing 6 genes takes about 30 minutes. TriAnnot is used within the framework of an international effort (International Wheat Genome Sequencing Consortium - IWGSC) for obtaining a reference sequence of the bread wheat genome. TriAnnot has already been used to annotate the wheat chromosome 3B (Choulet et al. 2014 Science) and 4D (Helguera et al. 2015 Plant Science). Annotation of chromosome 1B is currently underway (INRA - GDEC), as well as the annotation of chromosome 7A in collaboration with the University of Murdoch (Australia). TriAnnot has been used for the annotation of the 21 wheat chromosomes in parallel with MIPS in Germany. The TriAnnot source code has been strongly improved to facilitate its deployment on external computing resources such as: IEB, Olomouc (Czech Republic); CSIRO, Kensington (Australia); Mesocentre, Université Clermont Auvergne (UCA) and ABiMS CNRS bioinformatics platform, Roscoff (France). The development of a virtual machine is also underway in collaboration with ABiMS and the French Institute of bioinformatics (IFB).

The triAnnot pipeline is referenced within the omictools web site.

Publication :
Leroy P, Guilhot N, Sakai H, Bernard A, Choulet F, Theil S, Reboux S, Amano N, Flutre T, Pelegrin C, Ohyanagi H, Seidel M, Giacomoni F, Reichstadt M, Alaux M, Gicquello E, Legeai F, Cerutti L, Numa H, Tanaka T, Mayer K, Itoh T, Quesneville H, Feuillet C (2012) TriAnnot: a versatile and high performance pipeline for the automated annotation of plant genomes. Frontiers in Plant Sciences 3:1-14. doi:10.3389/fpls.2012.00005

Access conditions

Gratuit sur https://www6.inrae.fr/decodage/TriAnnot
Domains of activity
  • Biology
  • Agri-food
  • Environment
  • Biotechnology
  • Biomedical
Description of expertise domains

La plateforme fait apparaître une forte expertise en génomique, épigénomique et métagénomique. Les modèles biologiques sont variés (micro-organismes, plantes, animaux) donnant un caractère généraliste à de nombreux outils.
Cette plate-forme fait suite à une structuration des laboratoires de l'Université Clermont Auvergne faisant de la recherche dans ce domaine :

Keywords:
  • Analyse de données de séquençage NGS
  • Méthodologie
  • Assemblage de génomes et transcriptomes
  • Alignements de lectures sur des génomes
  • Analyse de génomes
  • Annotation structurale et fonctionnelle des génomes
  • Analyse différentielle de l’expression des gènes
  • Analyses de transcrits et transcrits variants
  • Panels (amplicons, captures)
  • Génomes complets
  • Analyse de la régulation de l’expression des gènes
  • Chip-seq
  • Petits et longs ARN non-codants
  • Profils de méthylation
  • Accessibilité de la chromatine
  • Analyse de la conformation des chromosomes
  • Métagénomique, métatranscriptomique
  • Algorithmique des séquences
  • Alignement (multiple) de séquences
  • Annotation de séquences
  • Recherche de motifs
  • Prédiction d'homologie/orthologie
  • Apprentissage automatique
  • Extraction de connaissances
  • Intégration de données hétérogènes
  • Représentation des connaissances
  • Ontologies
  • Web sémantique
  • Bioimagerie
  • Microscopie
  • Imagerie médicale
  • Analyse d’images
  • Bioinformatique structurale
  • Analyse des structures, recherche d'homologues et de motifs structuraux
  • Prédictions des propriétés structurales
  • Modélisation comparative et de novo de structures
  • Modélisation des interactions protéines/protéines, protéines/peptides et protéines/acides nucléiques
  • Biologie des systèmes
  • Génie métabolique
  • Modélisation des réseaux métaboliques
  • Modélisation des réseaux de régulation
  • Statistique descriptive
  • Tests statistiques
  • Régression
  • Analyses multivariées
  • Réduction de dimension
  • Statistique génétique
  • Cartographie génétique
  • Cartographie génétique et d'hybrides irradiés
  • Cartographie physique
  • Clonage positionnel
  • Localisation de QTL
  • Curation de collections de données
  • Outils
  • Intégration d'outils
  • Interfaces, portails web
  • Développement de workflows
  • Données
  • Intégration de données
  • Gestion et transfert de données
  • Bases de données et systèmes d’informations
  • Cluster
  • Cloud
  • GPU
  • Parallélisation
  • Ecologie
  • Génétique des populations
  • Biodiversité
  • Ecologie microbienne
  • Gènes et génomes
  • Paléogénomique et génomes ancestraux
  • Comparaison des génomes
  • Comparaison des voies fonctionnelles et régulatrices
  • Phylogénétiques
  • Génotypage
  • CGH
  • Fonctionelles
  • Expression
  • Tiling
  • Traitement du signal
  • Statistiques exploratoires
  • Statistiques inférentielles
  • Analyse des réseaux métaboliques
  • Identification des métabolites
  • Data identity and mapping (database search engine, spectral library search, de novo sequencing)
  • Inférence de protéine et validation
  • Protéomique quantitative
  • Analyse différentielle statistique
  • Protéogénomique
  • Démultiplexage de spectres
  • Analyse de second niveau
  • Analyse des modifications post-traductionnelles

Formation universitaire

Check the website
Trainees:
20 trainees / year
Training time:
1 day(s) / year
Upcoming session :
25-05-2016

Intégration d'outils dans Galaxy

Description
Galaxy (https://galaxyproject.org/) est une plateforme permettant d’intégrer et d’exécuter via une interface graphique des outils bioinformatiques, normalement utilisables en ligne de commande. Galaxy permet ainsi de faciliter l’utilisation de ces outils par tous, dans un environnement contrôlé,mais aussi de favoriser la reproductibilité des analyses (workflows, …).
Actuellement, > 3 750 outils (disponibles sur https://toolshed.g2.bx.psu.edu/) peuvent être intégrés à Galaxy. Mais tous les outils bioinformatiques dont vous pouvez avoir besoin ne sont pas intégrés dans 
l’environnement Galaxy. Et vous devez ainsi parfois renoncer à utiliser Galaxy et ses avantages pour traiter vos données.
Un workshop est organisé à Clermont-Ferrand le Mercredi 25 Mai 2016. 

N’hésitez pas à faire circuler cette information aux personnes potentiellement intéressées.
Merci par avance.
Bérénice BATUT

Access conditions
Not documented
No website documented
Trainees:
45 trainees / year
Training time:
Not documented
No upcoming session scheduled

DUT Bioinformatique

Description

A la convergence de la biologie, de l’informatique, cette formation pluridisciplinaire vise à former des techniciens supérieurs possédant une double compétence biologie/informatique capables de produire et de traiter des données biologiques de masse. La formation assurée en 2 ans vise à donner un socle solide de compétences transversales en biologie (génomique, transcriptomique, protéomique…), informatique (programmation, algorithmie, bioinformatiques structurale et intégrative ...) et statistiques, complétée par un travail en groupe ainsi qu’un stage de fin d’année en milieu professionnel. Axée sur les technologies « omiques », cette option propose une professionnalisation rapide pour un domaine en pleine croissance et donne des compétences solides pour  continuer vers un master ou un doctorat.

 

Access conditions

Accessible en formation continue pour des bacheliers des séries S, STL et en formation continue. Accessible directement en 2ème année pour des étudiants ayant validé une année dans le supérieur et ayant des compétences en biologie et des bases en programmation

 
No website documented
Trainees:
15 trainees / year
Training time:
Not documented
No upcoming session scheduled

Master Bio-informatique

Description

Forme au traitement et à l'analyse des données « à haut débit » (génomique, transcriptomique, protéomique, métabolomique). Cette formation inclus l’acquisition des connaissances fondamentales et des compétences opérationnelles liées à l’interprétation de ce type de données, à travers des enseignements de biologie, bioinformatique, informatique et statistiques appliquées à la Biologie. Elle se caractérise par une formation orientée vers le développement de web services et l’usage de ressources de calcul distribuées.

 

Access conditions

Licence de biologie / lic. Pro sur dossier
No website documented
Trainees:
250 trainees / year
Training time:
Not documented
No upcoming session scheduled

Licence 2 Science de la Vie

Description

2 UE fondamentales avec un enseignement de biostatistiques (statistiques descriptives, lois, tests, régression linéaire, analyse de variance) et bioinformatique (prédiction de gène, prédiction de fonction, bases de données bioinformatiques, alignement de séquences, phylogénie) en L2 et L3. Une UE optionnelle de programmation et bases de données relationnelles en L3.

 

Access conditions
Not documented
No website documented
Trainees:
180 trainees / year
Training time:
Not documented
No upcoming session scheduled

Licence 3 Science de la Vie

Description

2 UE fondamentales avec un enseignement de biostatistiques (statistiques descriptives, lois, tests, régression linéaire, analyse de variance) et bioinformatique (prédiction de gène, prédiction de fonction, bases de données bioinformatiques, alignement de séquences, phylogénie) en L2 et L3. Une UE optionnelle de programmation et bases de données relationnelles en L3.

 

Access conditions
Not documented
No website documented
Trainees:
3 trainees / year
Training time:
Not documented
No upcoming session scheduled

Modules Biologie École Doctorale SVSAE

Description

Les UE de bioinformatique de la spécialité AMD sont ouvertes aux doctorants de l'école doctorale SVSAE dans le cadre de leur formation doctorale. 3 UE sont particulièrement suivies : UE « Programmation en perl », UE « Bioistatistiques et programmation sous R » et UE « Génomique et bioinformatique ». Les formations continues proposées dans le domaine de la bioinformatique sont également ouvertes aux étudiants de l'Ecole Doctorale, et permettent de valider un module de biologie. Forme 2 à 3 doctorants par an.

 

Access conditions
Not documented

Formation professionnelle

No website documented
Trainees:
Not documented
Training time:
Not documented
No upcoming session scheduled

Formation continue CNRS

Description
  • Phylogénie moléculaire, introduction aux notions d'évolution moléculaire et de phylogénie.
  • Modèles d'évolution des séquences, méthodes de reconstruction phylogénétiques.
  • Recherche de séquences homologues (BLAST), alignement multiples et reconstructions phylogénétiques.
  • Evaluation de la pertinence des arbres (bootstrap).

 

Access conditions
Not documented
No website documented
Trainees:
Not documented
Training time:
Not documented
No upcoming session scheduled

Formation continue INRA

Description
  • Bioanalyse, analyse de séquences (alignement, blast), bases de données, analyse de NGS via galaxy (Chi-Seq, RNA-seq).
  • Fouille de texte et de données pour l'analyse de promoteurs et la construction de réseaux biologiques (réseau RULBI). Forme une dizaine de personnes par session.

 

Access conditions
Not documented
Internal publications
External publications
Publications with the hosting laboratory

2019 - Efficiently Mining Recurrent Substructures from Protein Three-Dimensional Structure Graphs. R. Saidi, W. Dhifli, M. Maddouri, and E.M. Nguifo. J. Comput. Biol., 26 (6), 561-571. doi:10.1089/cmb.2018.0171


2018 - ASaiM: a Galaxy-based framework to analyze microbiota data. Batut B, Gravouil K, Defois C, Hiltemann S, Brugère JF, Peyretaillade E, Peyret P. GigaScience 7(6). 10.1093/gigascience/giy057

 


2017 - Active microorganisms thrive among extremely diverse communities in cloud water. Amato P, Joly M, Besaury L, Oudart A, Taib N, Moné A, Deguillaume L, Delort AM and Debroas D. PLoS ONE 12(8):e0182869 10.1371/journal.pone.0182869

 


2016 -  Integrated data mining of transcriptomic and proteomic datasets to predict the secretome of adipose tissue and muscle in ruminants. Bonnet M, Tournayre J, and Cassar-Malek I. Molecular BioSystems 12:2722-2734 doi:10.1039/C6MB00224B

2016 - Genotyping by Sequencing Using Specific Allelic Capture to Build a High-Density Genetic Map of Durum Wheat. Holtz Y, Ardisson M, Ranwez V, Besnard A, Leroy P, Poux G, et al. PLoS ONE 115:e0154609

2016 - Probe Design Strategies for Oligonucleotide Microarrays. Parisot N, Peyretaillade E, Dugat-Bony E, Denonfoux J, Mahul A, Peyret P. Methods in Molecular Biology 1368:67-82 doi:10.1007/978-1-4939-3136-1_6

 


2015 - New insights into the wheat chromosome 4D structure and virtual gene order, revealed by survey pyrosequencing. Helguera M, Rivarola M, Clavijo B, Martis MM, Vanzetti LS, Gonzalez S, Garbus I, Leroy P, Hana S, Valarik M, Caccamo M, Dolezel D, Mayer KF, Feuillet C, Tranquilli G, Paniego N, Echenique VC. Plant Science 233:200-212

2015 - JOBIM 2015 - Journées Ouvertes en Biologie, Informatique et Mathématiques. In: Leroy P & Peyret P. Eds, Conférence Annuelle de Bioinformatique. INRA, Clermont-Ferrand 6-9 Juillet 2015, Université d’Auvergne ISBN 2-7380-1378-3 (paper version); ISBN 2-7380-1377-5 (numeric version)

2015 - Fat&MuscleDB : A database to understand tissue growth processes contributing to body or muscle composition. Tournayre J, Cassar-Malek I, Reichstadt M, Picard B, Kaspric N, Bonnet M.  In: Proceedings JOBIM 2015, 6-9 july 2015, Clermont-Ferrand, France, 8p, submission 73

2015 - ProteINSIDE to Easily Investigate Proteomics Data from Ruminants: Application to Mine Proteome of Adipose and Muscle Tissues in Bovine foetuses. Kaspric N, Picard B, Reichstadt M, Tournayre J, Bonnet M. PLoS ONE 10(5):e0128086 doi:10.1371/journal.pone.0128086; PubMed PMID: 26000831

2015 - Haplotype divergence and multiple candidate genes at Rphq2, a partial resistance QTL of barley to Puccinia hordei. Yeo FK, Wang Y, Vozabova T, Huneau C, Leroy P, Chalhoub B, Qi XQ, Niks RE, Marcel TC. Theor Appl Genet – doi:10.1007/s00122-015-2627-5

2015 - Protein Function Easily Investigated by Genomics Data Mining Using the ProteINSIDE Online Tool. Kaspric N, Reichstadt M, Picard B,  Tournayre J, and Bonnet M. Genomics and Computational Biology 1(1):e16  ISSN 2365-7154

 


2014 - Metavir 2: new tools for viral metagenome comparison and assembled virome analysis. Simon Roux, Jeremy Tournayre, Antoine Mahul, Didier Debroas, François Enault. BMC Bioinformatics 15(1):76

2014 - PhylOPDb: a 16S rRNA oligonucleotide probe database for prokaryotic identification. Faouzi Jaziri, Nicolas Parisot, Anis Abid, Jérémie Denonfoux, et al. Database : The Journal of Biological Databases and Curation bau036

2014 - Large scale explorative oligonucleotide probe selection for thousands of genetic groups on a computing grid: application to phylogenetic probe design using a curated small subunit ribosomal RNA gene database. Faouzi Jaziri, Eric Peyretaillade, Mohieddine Missaoui, Nicolas Parisot, et al. The Scientific World Journal 350487

2014 - Structural and functional partitioning of bread wheat chromosome 3B. Choulet C, Alberti A, Theil S, Glover N, Barbe V, Daron J, Pingault L, Sourdille P, Couloux A, Paux E, Leroy P, Mangenot S, Guilhot N, Le Gouis J, Balfourier F, Alaux M, Jamilloux V, Poulain J, Durand C, Bellec A, Gaspin C, Safar J, Dolezel J, Rogers J, Vandepoele K, Aury J-M, Mayer K, Berges H, Quesneville H, Wincker P, Feuillet C. Science 345:1249721-1-7, doi:10.1126/science.1249721

 


2013 - NucBase, an esay to use read mapper for small RNAs. Mobile DNA. Dufourt J, Pouchin P, Peyret P, Brasset E and Vaury C.  Mob DNA 4(1) doi: 10.1186/1759-8753-4-1

2013 - Phylogenetic affiliation of SSU rRNA genes generated by massively parallel sequencing: new insights into the freshwater protist diversity. Taib N, Mangot JF, Domaizon I, Bronner G, Debroas D.  PLoS One 8(3):e58950 doi:10.1371/journal.pone.0058950

2013 - dbWFA: a web-based database for functional annotation of Triticum aestivum transcripts. Vincent J, Dai Z, Ravel C, Choulet F, Mouzeyar S, Bouzidi MF, Agier M, Martre P. Database (Oxford) 10.1093/database/bat014

2013 - The Human Gut Chip “HuGChip”, an Explorative Phylogenetic Microarray for Determining Gut Microbiome Diversity at Family Level. Tottey W, Denonfoux J, Jaziri F, Parisot N, Missaoui M, Hill DRC, Borrel G, Peyretaillade E, Alric M, Harris HMB, Jeffery IB, Claesson MJ, O'Toole PW, Peyret P, Brugère J-F.  PLoS One 8: e62544. doi:10.1371/journal.pone.0062544

 

 

 


 

2012 - Annotation of microsporidian genomes using transcriptional signals. Peyretaillade E, Parisot N, Polonais V, Terrat S, et al. Nature Communications, 3:1137

2012 - TriAnnot: a versatile and high performance pipeline for the automated annotation of plant genomes. Leroy P, Guilhot N, Sakai H, Bernard A, Choulet F, Theil S, Reboux S, Amano N, Flutre T, Pelegrin C, Ohyanagi H, Seidel M, Giacomoni F, Reichstadt M, Alaux M, Gicquello E, Legeai F, Cerutti L, Numa H, Tanaka T, Mayer K, Itoh T, Quesneville H, Feuillet C.  Frontiers in Plant Sciences 3:1-14

 
Users distribution
International
10 %
National
10 %
Regional
10 %
Local
70%
Explanation about this distribution:

La plate-forme est nouvellement créée et de ce fait les pourcentages reflètent les activités au travers du CRRI et des différents partenaires.
Platform's own projects
(4)

Not Documented
Collaborations
National projets
(4)
Not documented
International and European projects
(1)
Not documented
Projets with industry
(3)
Not documented
Collaboration projects not founded through an external organism
Not documented
Provision of services not founded through an external organism
(40)
- spécifications des besoins
 - support au déploiement et à l’utilisation des ressources
 - hébergement VM ou serveurs physiques Conditions d’appui à des projets et d’hébergement : sur projet
Animations (Workshops, Work-groups, seminars, conferences ... )

Réunions.
Invitations de conférenciers.
Organisation de congrès (JOBIM 2015)
Ateliers et formations
Création d’un groupe d’utilisateurs pour le mésocentre
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