Olivier Poch

    Olivier Poch    olivier.poch@unistra.fr    Fed DBGS    /~poch    /wikili/index.php/Olivier_Poch

Responsible of following 2 workpackages :

WP-LBGI : Laboratoire de BioInformatique et Genomique Intégratives : WP-LBGI : Laboratoire de BioInformatique et Genomique Intégratives

    Responsible : Olivier Poch
    Participants : Alexis Allot, Carlos Bermejo-Das-Neves, Kirsley Chennen, Arnaud Kress, Odile Lecompte, Luc Moulinier, Jean Muller, Yannis Nevers, Anne Ney, Olivier Poch, Laetitia Poidevin, Wolfgang Raffelsberger, Raymond Ripp, Raphaël Schneider, Julie Thompson, Renaud Vanhoutreve, Catherine Guth, Pierre Collet, Anne Jeannin, Pierre Parrend
    Description : Ce workpackage est tout LBGI BioInformatique et Génomique Intégatives

Instruct Bioinformatics : Instruct Bioinformatics

    Responsible : Olivier Poch, Raymond Ripp, Julie Thompson
    Participants : Olivier Poch, Raymond Ripp, Julie Thompson
    Description :

Participates to following workpackages :

LungCancerCGH : LungCancerCGH

    Responsible : Wolfgang Raffelsberger
    Participants : Olivier Poch, Wolfgang Raffelsberger
    Description : Prognistic and predictive values of high-resolution molecular DNA markers in non-small cell lung cancers (NSCLC) of IFCT-00-02 trial (phase III studycomparing a reoperative and chemotherapy with two different chemotherapy regimes in resectable NSCLC)
Acronym: BIO IFCT-00-02 II
Collaboriation with M Beau-Faller and P Oudet (Hautpierre)

H1PVRNAi : H1PVRNAi

    Responsible : Wolfgang Raffelsberger
    Participants : Olivier Poch, Wolfgang Raffelsberger
    Description : Oncolytic H-1 ParvoVirus RNAi screen INCa platform project; LBGI/Bips (O Poch, W Raffelsberger) in collaboration with high-throughput transfection platform (P Oudet/L Brino), Inserm Unité 701 (DKFZ) (A Marchini) and transcriptomics platform IGBMC (P Kastner).
De part leur tropisme naturel pour les cellules tumorales, leur activité oncolytique et l’absence de symptomes lors d’infections chez l’homme, les petits virus de la famille des parvovirus (type MVM, H1 et LuIII) présentent un grand potentiel pour le développement de nouvelles stratégies de traitement du cancer.
La protéine non structurale NS1 est essentielle pour la réplication de l’ADN viral, l’expression de gènes viraux et est un des effecteurs majeurs de l’activité oncolytique des parvovirus.
Cependant, la connaissance du cycle de vie de ces virus, des facteurs cellulaires impliqués et des mécanismes oncolytiques associés reste fragmentaire.
Les objectifs :
i) identifier et caractériser fonctionnellement les déterminants moléculaires impliqués dans les étapes précoces de l’entrée et de la transduction des parvovirus,
ii) identifier les voies cellulaires activées en réponse à l’infection virale et notamment celles impliquées dans leur activité oncolytique.

EvolHHuPro : EvolHHuPro

    Responsible : Julie Thompson
    Participants : Benjamin Linard, Olivier Poch, Julie Thompson
    Description : The genetic information encoded in the genome sequence contains the blueprint for the potential development and activity of an organism. This information can only be fully comprehended in the light of the evolutionary events (duplication, loss, recombination, mutation…) acting on the genome, that are reflected in changes in the sequence, structure and function of the gene products (nucleic acids and proteins) and ultimately, in the biological complexity of the organism.
The recent availability of the complete genome sequences of a large number of model organisms means that we can now begin to understand the mechanisms involved in the evolution of the genome and their consequences in the study of biological systems. This is illustrated by the evolutionary analyses and phylogenetic inferences that play an important role in most functional genomics studies, e.g. of promoters (‘phylogenetic footprinting’), of interactomes (notion of ‘interologs’ based on the presence and degree of conservation of counterparts of interactive proteins), and also, in comparisons of transcriptomes or proteomes (notion of phylogenetic proximity and co-regulation/co-expression).
At the same time, theoretical advances in information representation and management have revolutionised the way experimental information is collected, stored and exploited. Ontologies, such as Gene Ontology (GO) or Sequence Ontology (SO), provide a formal representation of the data for automatic, high-throughput data parsing by computers. These ontologies are being exploited in the new information management systems to allow large scale data mining, pattern discovery and knowledge inference.
Unfortunately, the vast number and complexity of the events shaping eukaryotic genomes means that a complete understanding of evolution at the genomic level is not currently feasible. At the lowest level, point mutations affect individual nucleotides. At a higher level, large chromosomal segments undergo duplication, lateral transfer, inversion, transposition, deletion and insertion. Ultimately, whole genomes are involved in processes of hybridization, polyploidization and endosymbiosis, often leading to rapid speciation.
We will characterise and study the evolutionary histories of the human proteome, defined as the impact in the human proteins (extensions, insertions, deletions…) of the cascade of genetic events (duplication, lateral transfer, inversion, transposition, deletion, insertion…) that occurred during the evolution of the vertebrate genomes. This ambitious objective is now possible thanks to the emergence of formal descriptions of biological data and to the recent developments of accurate phylogenetic reconstruction and genome analyses (Partner 1: Figenix platform) and of automated reliable and exploitable protein sequence alignments (TCOFFEE, PipeAlign, MAO, MACSIMS…). These methodologies will be combined into a multi-agent, expert system for the construction of evolutionary histories. In order to facilitate the automatic definition of the important genetic events shaping a single protein and their potential causalities at the genome level, a new ontology will be developed. In a subsequent step, the evolutionary histories of the complete human proteome will be reconstructed, followed by their classification into protein sets sharing typical evolutionary histories, and the functional analysis of these sets. An analysis at the genomic level will be realized for a specific number of proteins identified in the classification and functional analysis step.

GenoretGenes : GenoretGenes

    Responsible : Laetitia Poidevin
    Participants : Olivier Poch, Laetitia Poidevin, Raymond Ripp
    Description :

Alvinella pompejana : Alvinella pompejana

    Responsible : Nicolas Gagnière, Odile Lecompte
    Participants : Odile Lecompte, Olivier Poch, Raymond Ripp
    Description :