Next-generation global biomonitoring: large-scale, automated reconstruction of ecological networks
| hal.structure.identifier | Agroécologie [Dijon] | |
| dc.contributor.author | BOHAN, David | |
| hal.structure.identifier | Biodiversité, Gènes & Communautés [BioGeCo] | |
| dc.contributor.author | VACHER, Corinne | |
| hal.structure.identifier | Computational Bioinformatics Laboratory, Department of Computing | |
| dc.contributor.author | TAMADDONI-NEZHAD, Alireza | |
| hal.structure.identifier | Syngenta | |
| dc.contributor.author | RAYBOULD, Alan | |
| hal.structure.identifier | School of Biological Sciences [Colchester] | |
| dc.contributor.author | DUMBRELL, Alex J | |
| hal.structure.identifier | Department of Life Sciences [Trieste] | |
| dc.contributor.author | WOODWARD, Guy | |
| dc.date.issued | 2017 | |
| dc.identifier.issn | 0169-5347 | |
| dc.description.abstractEn | We foresee a new global-scale, ecological approach to biomonitoring emerging within the next decade that can detect ecosystem change accurately, cheaply, and generically. Next-generation sequencing of DNA sampled from the Earth's environments would provide data for the relative abundance of operational taxonomic units or ecological functions. Machine-learning methods would then be used to reconstruct the ecological networks of interactions implicit in the raw NGS data. Ultimately, we envision the development of autonomous samplers that would sample nucleic acids and upload NGS sequence data to the cloud for network reconstruction. Large numbers of these samplers, in a global array, would allow sensitive automated biomonitoring of the Earth's major ecosystems at high spatial and temporal resolution, revolutionising our understanding of ecosystem change. | |
| dc.description.sponsorship | Predicting and enhancing the Resilience of European Agro-ecosystems to environmental change using crop Rotations - ANR-15-SUSF-0002 | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.rights.uri | http://creativecommons.org/licenses/by-sa/ | |
| dc.subject | biosurveillance | |
| dc.subject | séquençage adn | |
| dc.subject | changement d'ecosystème | |
| dc.title.en | Next-generation global biomonitoring: large-scale, automated reconstruction of ecological networks | |
| dc.type | Article de revue | |
| dc.identifier.doi | 10.1016/j.tree.2017.03.001 | |
| dc.subject.hal | Sciences du Vivant [q-bio] | |
| bordeaux.journal | Trends in Ecology & Evolution | |
| bordeaux.page | 477-487 | |
| bordeaux.volume | 32 | |
| bordeaux.issue | 7 | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-01606909 | |
| hal.version | 1 | |
| hal.popular | non | |
| hal.audience | Non spécifiée | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-01606909v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Trends%20in%20Ecology%20&%20Evolution&rft.date=2017&rft.volume=32&rft.issue=7&rft.spage=477-487&rft.epage=477-487&rft.eissn=0169-5347&rft.issn=0169-5347&rft.au=BOHAN,%20David&VACHER,%20Corinne&TAMADDONI-NEZHAD,%20Alireza&RAYBOULD,%20Alan&DUMBRELL,%20Alex%20J&rft.genre=article |
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