首页> Microbiology spectrum> Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy.

Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy.

导出 LinkOut

翻译打印收藏纠错

第一作者： Rohan,Khan

第一单位： Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada.

作者： Rohan,Khan ^[1] ; Tulika,Bhardwaj ^[1] ; Carmen,Li ^[1] ; Anirban,Chakraborty ^[2] ; José M,Seoane ^[3] ; James M,Brooks ^[4] ; Bernie B,Bernard ^[4] ; Adam,MacDonald ^[5] ; Natasha,MacAdam ^[5] ; Calvin,Campbell ^[6] ; Martin,Fowler ^[7] ; Casey R J,Hubert ^[1]

作者单位： Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada. ^[1] Department of Biological Sciences, Idaho State University, Pocatello, Idaho, USA. ^[2] Repsol SA, Madrid, Spain. ^[3] TDI-Brooks International, College Station, Texas, USA. ^[4] Natural Resources Canada, Geological Survey of Canada Atlantic, Dartmouth, Canada. ^[5] Nova Scotia Department of Natural Resources and Renewables, Government of Nova Scotia, Halifax, Canada. ^[6] Applied Petroleum Technology Canada, Calgary, Alberta, Canada. ^[7]

关键词 16S rRNA environmental microbiology hydrocarbons machine learning marine cold seeps

医学主题词地质沉积物(Geologic Sediments);烃类(Hydrocarbons);RNA, 核糖体, 16S(RNA, Ribosomal, 16S);细菌(Bacteria);种系发生(Phylogeny);海水(Seawater);DNA, 细菌(DNA, Bacterial)

DOI 10.1128/spectrum.03033-24

PMID 40833080

发布时间 2025-10-09

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交