L’UMR CBGP – Centre de Biologie pour la Gestion des Populations – a pour vocation de comprendre les mécanismes qui régissent l’évolution de populations d'organismes importants pour l’agronomie, les forêts, la santé humaine ou la conservation de la biodiversité. Les recherches portent sur des modèles biologiques et sont développées selon six axes : origine et caractérisation de la biodiversité ; adaptation des phytophages, de leurs ennemis naturels et de leurs symbiontes ; écologie et évolution des zoonoses ; biologie, écologie et évolution des espèces envahissantes ; génomique statistique et évolutive des populations ; approches moléculaires et bioinformatiques haut débit. Nos tutelles sont l'INRAE, le CIRAD, l'IRD et l'Institut Agro-Montpellier.

UMR CBGP – Centre de Biologie pour la Gestion des Populations – aims to understand the mechanisms that govern populations of organisms that are important to agriculture, forest, human health and biodiversity conservation. Studies concern biological models and follow six lines of research: origin and characterization of biodiversity; adaptation of plant eaters, their natural enemies and symbionts; ecology and evolution of zoonoses; biology, ecology and evolution of invasive species; statistical and evolutionary population genomics; and high-throughput molecular and bioinformatics techniques. Our supervising bodies are INRAE, CIRAD, IRD and Institut Agro-Montpellier.
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81 to 90 of 130 Results
Comma Separated Values - 55,3 KB - MD5: 405f4884b31c5a813d524ed71e0bae62
DataGC-MS
Chemical analyses (GC-MS) data.
Comma Separated Values - 20,0 KB - MD5: b20183ac349db0281cae41b9b7cacf7f
DataGC-MS
Filtered VOCs, to be analyzed by L3_GCMS_analysis.R. Data generated byL3_GCMS_filters.R script.
R Syntax - 7,9 KB - MD5: e4913e31513b11b5849ec798c86c6ca3
CodeGC-MSR
R script for GC-MS analysis.
R Syntax - 3,8 KB - MD5: a0834b9f20351b50442b49d050bd74fe
CodeGC-MSR
R script to filter VOCs.
R Syntax - 13,5 KB - MD5: 913281e2681925398c0bf98ee234b8da
Behavioural assaysCodeR
R script for behavioural assays analysis and statistical tests.
Plain Text - 1,0 KB - MD5: f7c416771f101e1bef4ed356f43bdf77
Behavioural assaysDocumentationGC-MS
Files documentation.
Tabular Data - 409 B - 1 Variables, 25 Observations - UNF:6:CQg5G7emWL6qao1Wk7YhuQ==
DataGC-MS
Reference table of samples analyzed in GC-MS.
29 août 2022
Javal, Marion; Terblanche, John; Benoit, Laure; Conlong, Desmond; Lloyd, James; Chapuis, Marie-Pierre, 2022, "Original data for "Javal et al. 2022. Does host plant drive variation in microbial gut communities in a recently shifted pest? Microbial Ecology (2022)"", https://doi.org/10.18167/DVN1/4KYM3B, CIRAD Dataverse, V1, UNF:6:hw/k9VXTEae1/JbguJzMtQ== [fileUNF]
Dataset describing microbial gut communities in a recently shifted pest, Cacosceles newmannii in 2018 in Kwazulu Natal, South Africa.
Plain Text - 3,8 KB - MD5: 84ef1e8ba0e656d5b52f7065d68131fc
Metadata of the abundance table of the 100 hundred gut samples used in statistical analyses.
Unknown - 132,9 KB - MD5: 9f24a065265a74496f74d87f16fa55d7
Fasta file of bacterial sequences retained after filtering
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