Olivier Dameron

Institut de Recherche en Informatique et Systèmes Aléatoires

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Anita Burgun

Institut des Maladies Génétiques Imagine

Anne Siegel

Université de Rennes

Bernard Gibaud

Université de Rennes

Alice Fatet

Physiologie de la Reproduction et des Comportements

Matthieu Reichstadt

Université Clermont Auvergne

Catherine Hurtaud

Institut Agro Rennes-Angers

Isabelle Hue

Fish Physiology and Genomics Institute

Jérôme Bugeon

Fish Physiology and Genomics Institute

Charles Bettembourg

Sanofi (France)

Claire Nédellec

Mathématiques et Informatique Appliquées du Génome à l'Environnement

Cooperative Institutions

Centre National de la Recherche Scientifique

102

Université de Rennes

Inserm

Institut de Recherche en Informatique et Systèmes Aléatoires

Institut national de recherche en informatique et en automatique

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Institut National de la Recherche Agronomique

Centre Hospitalier Universitaire de Rennes

Sorbonne Université

Institut Agro Rennes-Angers

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OWL Model of Clinical Trial Eligibility Criteria Compatible with Partially-known Information.

SWAT4LS (2012)

Olivier Dameron Paolo Besana Oussama Zékri Annabel Bourdé Anita Burgun

Background Clinical trials are important for patients, for researchers and for companies. One of the major bottlenecks is patient recruitment. This task requires the matching of a large volume of information about the patient with numerous eligibility criteria, in a logically-complex combination. Moreover, some of the patient’s information necessary to determine the status of the eligibility criteria may not be available at the time of pre-screening.

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Using Semantic dependencies for consistency Management of an ontology of brain-cortex anatomy

Olivier Dameron Bernard Gibaud Mark A. Musen

In the context of the Semantic Web, ontologies have to be usable by software agents as well as by humans. Therefore, they must meet explicit representation and consistency requirements. This article describes a method for managing the semantic consistency of an ontology of brain-cortex anatomy. The methodology relies on the explicit identification of the relationship properties and of the dependencies that might exist among concepts or relationships. These dependencies have to be respected for insuring the semantic consistency of the model. We propose a method for automatically generating all the dependent items. As a consequence, knowledge base updates are easier and safer. Our approach is composed of three main steps: (1) providing a realistic representation, (2) ensuring the intrinsic consistency of the model and (3) checking its incremental consistency. The corner stone of ontological modeling lies in the expressiveness of the model and in the sound principles that structure it. This part defines the ideal possibilities of the ontology and is called realism of representation. Regardless of how well a model represents reality, the intrinsic consistency of a model corresponds to its lack of contradiction. This step is particularly important as soon as dependencies between relationships or concepts have to be fulfilled. Eventually, the incremental consistency encompasses the respect of the two previous criteria during the successive updates of the ontology.

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AuReMe: an integrative method for the automatic reconstruction of metabolic networks

F1000Research (2014)

Jeanne Cambefort Guillaume Collet Sylvain Prigent Simon M. Dittami Olivier Dameron

Open peer review

10.7490/f1000research.1096893.1

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Cross-species metabolic pathways comparison: Focus on mouse, human and chicken lipid metabolism

HAL (Le Centre pour la Communication Scientifique Directe) (2011)

Charles Bettembourg Christian Diot Olivier Dameron

Metabolic pathway

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OUP accepted manuscript

Database (2021)

Vincent Henry Ivan Moszer Olivier Dameron Laura Xicota Bruno Dubois

Omics technologies offer great promises for improving our understanding of diseases.The integration and interpretation of such data pose major challenges, calling for adequate knowledge models.Disease maps provide curated knowledge about disorders' pathophysiology at the molecular level adapted to omics measurements.However, the expressiveness of disease maps could be increased to help avoiding ambiguities and misinterpretations and to reinforce their interoperability with other knowledge resources.Ontologies are an adequate framework to overcome this limitation, through their axiomatic definitions and logical reasoning properties.We introduce the Disease Map Ontology (DMO), an ontological upper model based on systems biology terms.We then propose to apply DMO to Alzheimer's disease (AD).Specifically, we use it to drive the conversion of AlzPathway, a disease map devoted to Alzheimer's disease, into a formal ontology: AD Map Ontology (ADMO).We demonstrate that it allows one to deal with issues related to redundancy, naming, consistency, process classification and pathway relationships.Furthermore, we show that it can store and manage multi-omics data.Finally, we expand the model using elements from other resources, such as clinical features contained in the ADO (AD Ontology), resulting in an enriched model called ADMO-plus.The current versions of DMO, ADMO and ADMOplus are freely available at http://bioportal.bioontology.org/ontologies/ADMO.

Formal ontology

Open Biomedical Ontologies

10.1093/database/baab004

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Atol and eol ontologies, step towards embryonic phenotypes shared worldwide?

HAL (Le Centre pour la Communication Scientifique Directe) (2013)

Isabelle Hue Jérôme Bugeon Olivier Dameron Alice Fatet Catherine Hurtaud

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PEPS: a platform for supporting studies in pharmaco-epidemiology using medico-administrative databases

HAL (Le Centre pour la Communication Scientifique Directe) (2016)

Frédéric Balusson Marie-Anne Botrel Olivier Dameron Yann Dauxais Erwan Drézen

Background: New approaches of pharmaco-epidemiology consist in using large EHR databases to investigate the effects and uses (or misuses) of drugs in real conditions. The objective is to benefit from nationwide available data to answer accurately and in a short time pharmaco-epidemiological queries for national public health institutions. Despite the potential availability of the data, their size and complexity make their analysis long and tremendous. The challenge we tackle is the conception of a generic digital toolbox to support the efficient design of a broad range of pharmaco-epidemiology studies from EHR databases. Methods: To be able to answer the broad range of pharmaco-epidemiological queries from national public health institutions, the PEPS platform exploits, in secondary use, the French health cross-schemes insurance system, called SNIIRAM. The SNIIRAM covers most of the French population with a sliding period of 3 past years. To tackle the volume and the diversity of the SNIIRAM data warehouse, a research program has been established to design an innovative toolbox. This research program is focused first on the modeling of care pathways from the SNIIRAM database and, second, on the design of tools supporting meaningful insights extraction about massive and complex care pathways by clinicians. Results: A data infrastructure has been set up to collect and to access the data securely. We proposed and developed a high level abstraction model to access and to visualize care pathways. We designed the principle of a toolbox to carry out generic pharmaco-epidemiological studies from the SNIIRAM data warehouse (see figure). This toolbox is oriented toward data analytics with data visualisation, domain specific query language, knowledge discovery and statistics modules. Conclusions: The preliminary results on the development of the PEPS platform show that our care pathways model is very expressive and that it allows to have a highly abstracted representation of the warehouse's complex data. Our modular architecture supports clinicians and epidemiologists all along their analysis process.

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État des lieux MoDaL (Multi-Scale Data Links)

HAL (Le Centre pour la Communication Scientifique Directe) (2020)

Aurélien Cornet Christian Barillot Olivier Dameron Alban Gaignard Camille Maumet

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BIPAA/Askomics, a new and easy approach for querying genomics and epigenomics elements in interaction

2016 International Congress of Entomology (2016)

Fabrice Legeai Charles Bettembourg Anthony Bretaudeau Yvanne Chaussin Olivier Dameron

Research programs involving genetic, genomic and epigenetic of have become fast growing areas of biology. Once the computational challenges of analyzing datasets have been dealt with; large and complex biological data still remain in the hands of biologists for interpretation. Projects such as Biomart and Intermine have been developed to facilitate exchange and comparison of complex biological data; however access and interrogation can be time consuming for biologists and integrate all publicly available data still remains a challenge. Moreover for non-model organisms; large heterogeneous biological datasets can be difficult to associate in order to obtain a comprehensive view. The notion of “linked data” from semantic technologies benefits to biologists. Using RDF (Reference Description Framework); biological data can be stored in triples (subject, predicate, object) that define a relationship between two entities. Thanks to the SPARQL query language, RDF data can be queried to join different datasets. Nevertheless, understanding and acquiring the query language can be a daunting task for biologists. Here we present AskOmics, a tool supporting both intuitive data integration and querying while shielding the user from most of the technical difficulties underlying RDF and SPARQL. For data integration, the user loads his data as tabulation-separated files structured according to simple principles. This structure allows AskOmics to generate automatically RDF triples, and to store them. Finally, for data querying, AskOmics provides a visually intuitive interface. AskOmics has been applied successfully to the analysis of large scale datasets including lncRNA, miRNA, piRNA and transcriptomic profiles of the aphid embryogenesis.

Biological data

10.1603/ice.2016.89534

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Développement et évaluation d’un algorithme de représentation des parcours de soins de patientes atteintes de cancer du sein à partir des données d’un système d’information régional

Revue d Épidémiologie et de Santé Publique (2013)

Anne‐Julia Rollet Gautier Défossez Olivier Dameron CoRIM Poitou-Charentes CRISAP Poitou-Charentes

10.1016/j.respe.2013.01.041

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