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Learning ecological networks from next-generation sequencing data

hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
dc.contributor.authorVACHER, Corinne
hal.structure.identifierDepartment of Computing
dc.contributor.authorTAMADDONI-NEZHAD, Alireza
hal.structure.identifierInstitut de Génétique, Environnement et Protection des Plantes [IGEPP]
hal.structure.identifierUniversity of Guelph
dc.contributor.authorKAMENOVA, Stefaniya
hal.structure.identifierUnité de Mathématiques et Informatique Appliquées de Toulouse [MIAT INRA]
dc.contributor.authorDUBOIS PEYRARD, Nathalie
hal.structure.identifierLaboratoire de Microbiologie des Environnements Extrêmophiles [LM2E]
hal.structure.identifierInstitut Universitaire Européen de la Mer [IUEM]
dc.contributor.authorMOALIC, Yann
hal.structure.identifierUnité de Mathématiques et Informatique Appliquées de Toulouse [MIAT INRA]
dc.contributor.authorSABBADIN, Régis
hal.structure.identifierMathématiques et Informatique Appliquées [MIA-Paris]
hal.structure.identifierAgroParisTech
dc.contributor.authorSCHWALLER, Loïc
hal.structure.identifierLaboratoire de Mathématiques et Modélisation d'Evry [LaMME]
dc.contributor.authorCHIQUET, Julien
hal.structure.identifierUniversity of Guelph
dc.contributor.authorALEX SMITH, M.
hal.structure.identifierUnité Mixte de Recherche en Santé Végétale (INRA/ENITA) [UMRSV]
dc.contributor.authorVALLANCE, Jessica
hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
dc.contributor.authorFIEVET, Virgil
hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
dc.contributor.authorJAKUSCHKIN, Boris
hal.structure.identifierAgroécologie [Dijon]
dc.contributor.authorBOHAN, David
dc.date.issued2016
dc.description.abstractEnSpecies diversity, and the various interactions that occur between species, supports ecosystems functioning and benefit human societies. Monitoring the response of species interactions to human alterations of the environment is thus crucial for preserving ecosystems. Ecological networks are now the standard method for representing and simultaneously analyzing all the interactions between species. However, deciphering such networks requires considerable time and resources to observe and sample the organisms, to identify them at the species level and to characterize their interactions. Next-generation sequencing (NGS) techniques, combined with network learning and modelling, can help alleviate these constraints. They are essential for observing cryptic interactions involving microbial species, as well as short-term interactions such as those between predator and prey. Here, we present three case studies, in which species associations or interactions have been revealed with NGS. We then review several currently available statistical and machine-learning approaches that could be used for reconstructing networks of direct interactions between species, based on the NGS co-occurrence data. Future developments of these methods may allow us to discover and monitor species interactions cost-effectively, under various environmental conditions and within a replicated experimental design framework.
dc.language.isoen
dc.source.titleEcosystem Services: From Biodiversity to Society, Part 2
dc.subjectécosystème
dc.subjectréseau écologique
dc.subjectdiscipline scientifique
dc.subjectréseau de competence
dc.subjectbiodiversité
dc.subject.enmicrobial network
dc.subject.enfood web
dc.subject.enecological network
dc.subject.enscientific discipline
dc.subject.enbiodiversity
dc.subject.enspecies interactions
dc.subject.ennext-generation sequencing
dc.subject.enbarcoding
dc.subject.ennetwork inference
dc.subject.enmachine learning
dc.subject.enecosystem
dc.title.enLearning ecological networks from next-generation sequencing data
dc.typeChapitre d'ouvrage
dc.identifier.doi10.1016/bs.aecr.2015.10.004
dc.subject.halSciences du Vivant [q-bio]
bordeaux.pagenp
bordeaux.volume54
bordeaux.title.proceedingEcosystem Services: From Biodiversity to Society, Part 2
hal.identifierhal-01533861
hal.version1
hal.popularnon
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01533861v1
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