Predicting the ecological quality status of marine environments from eDNA metabarcoding data using supervised machine learning

T Cordier, P Esling, F Lejzerowicz, J Visco… - … science & technology, 2017 - ACS Publications
Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic
activities in marine environments. Traditionally, marine biomonitoring involves the sorting …
被引用次数：190 相关文章

Predicting the ecological quality status of marine environments from eDNA metabarcoding data using supervised machine learning

T Cordier, P Esling, F Lejzerowicz… - Environmental Science …, 2017 - hal.science
Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic
activities in marine environments. Traditionally, marine biomonitoring involves the sorting …

Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning.

T Cordier, P Esling, F Lejzerowicz, J Visco… - Environmental science & …, 2017 - sonar.ch
English Monitoring biodiversity is essential to assess the impacts of increasing
anthropogenic activities in marine environments. Traditionally, marine biomonitoring …
[PDF] academia.edu

[PDF][PDF] Predicting the ecological quality status of marine environments from eDNA metabarcoding data using supervised machine learning

T Cordier, P Esling, F Lejzerowicz, J Visco, A Ouadahi… - academia.edu
Table S8: Accuracy of BI values predictions from composition data, as a function of
abundance filtering on the OTU-to-sample matrix. R2 values are indicated and kappa …

Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning

T Cordier, P Esling, F Lejzerowicz, J Visco… - … Science & Technology …, 2017 - pure.au.dk
Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic
activities in marine environments. Traditionally, marine biomonitoring involves the sorting …
[PDF] researchgate.net

[PDF][PDF] Predicting the ecological quality status of marine environments from eDNA metabarcoding data using supervised machine learning

T Cordier, P Esling, F Lejzerowicz, J Visco, A Ouadahi… - researchgate.net
Table S8: Accuracy of BI values predictions from composition data, as a function of
abundance filtering on the OTU-to-sample matrix. R2 values are indicated and kappa …

[引用][C] Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning

T Cordier, P Esling, F Lejzerowicz, J Visco… - … Science & Technology, 2017 - cir.nii.ac.jp
Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding
Data Using Supervised Machine Learning | CiNii Research CiNii 国立情報学研究所 学術情報 …

Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning.

T Cordier, P Esling, F Lejzerowicz, J Visco… - … science & technology, 2017 - folia.unifr.ch
English Monitoring biodiversity is essential to assess the impacts of increasing
anthropogenic activities in marine environments. Traditionally, marine biomonitoring …

Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning

T Cordier, P Esling, F Lejzerowicz… - Environmental …, 2017 - pubmed.ncbi.nlm.nih.gov
Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic
activities in marine environments. Traditionally, marine biomonitoring involves the sorting …

Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning.

T Cordier, P Esling, F Lejzerowicz, J Visco… - Environmental …, 2017 - europepmc.org
Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic
activities in marine environments. Traditionally, marine biomonitoring involves the sorting …