Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy.
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| Title: | Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy. |
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| Authors: | Khan R; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada., Bhardwaj T; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada., Li C; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada., Chakraborty A; Department of Biological Sciences, Idaho State University, Pocatello, Idaho, USA., Seoane JM; Repsol SA, Madrid, Spain., Brooks JM; TDI-Brooks International, College Station, Texas, USA., Bernard BB; TDI-Brooks International, College Station, Texas, USA., MacDonald A; Natural Resources Canada, Geological Survey of Canada Atlantic, Dartmouth, Canada., MacAdam N; Natural Resources Canada, Geological Survey of Canada Atlantic, Dartmouth, Canada., Campbell C; Nova Scotia Department of Natural Resources and Renewables, Government of Nova Scotia, Halifax, Canada., Fowler M; Applied Petroleum Technology Canada, Calgary, Alberta, Canada., Hubert CRJ; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada. |
| Source: | Microbiology spectrum [Microbiol Spectr] 2025 Oct 07; Vol. 13 (10), pp. e0303324. Date of Electronic Publication: 2025 Aug 20. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: ASM Press Country of Publication: United States NLM ID: 101634614 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2165-0497 (Electronic) Linking ISSN: 21650497 NLM ISO Abbreviation: Microbiol Spectr Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40833080 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Khan+R%22">Khan R</searchLink>; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada.<br /><searchLink fieldCode="AU" term="%22Bhardwaj+T%22">Bhardwaj T</searchLink>; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada.<br /><searchLink fieldCode="AU" term="%22Li+C%22">Li C</searchLink>; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada.<br /><searchLink fieldCode="AU" term="%22Chakraborty+A%22">Chakraborty A</searchLink>; Department of Biological Sciences, Idaho State University, Pocatello, Idaho, USA.<br /><searchLink fieldCode="AU" term="%22Seoane+JM%22">Seoane JM</searchLink>; Repsol SA, Madrid, Spain.<br /><searchLink fieldCode="AU" term="%22Brooks+JM%22">Brooks JM</searchLink>; TDI-Brooks International, College Station, Texas, USA.<br /><searchLink fieldCode="AU" term="%22Bernard+BB%22">Bernard BB</searchLink>; TDI-Brooks International, College Station, Texas, USA.<br /><searchLink fieldCode="AU" term="%22MacDonald+A%22">MacDonald A</searchLink>; Natural Resources Canada, Geological Survey of Canada Atlantic, Dartmouth, Canada.<br /><searchLink fieldCode="AU" term="%22MacAdam+N%22">MacAdam N</searchLink>; Natural Resources Canada, Geological Survey of Canada Atlantic, Dartmouth, Canada.<br /><searchLink fieldCode="AU" term="%22Campbell+C%22">Campbell C</searchLink>; Nova Scotia Department of Natural Resources and Renewables, Government of Nova Scotia, Halifax, Canada.<br /><searchLink fieldCode="AU" term="%22Fowler+M%22">Fowler M</searchLink>; Applied Petroleum Technology Canada, Calgary, Alberta, Canada.<br /><searchLink fieldCode="AU" term="%22Hubert+CRJ%22">Hubert CRJ</searchLink>; Geomicrobiology Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101634614%22">Microbiology spectrum</searchLink> [Microbiol Spectr] 2025 Oct 07; Vol. 13 (10), pp. e0303324. <i>Date of Electronic Publication: </i>2025 Aug 20. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22ASM+Press%22">ASM Press </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101634614 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2165-0497 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2221650497%22">21650497 </searchLink><i>NLM ISO Abbreviation: </i>Microbiol Spectr <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40833080 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1128/spectrum.03033-24 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: e0303324 Titles: – TitleFull: Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Khan R – PersonEntity: Name: NameFull: Bhardwaj T – PersonEntity: Name: NameFull: Li C – PersonEntity: Name: NameFull: Chakraborty A – PersonEntity: Name: NameFull: Seoane JM – PersonEntity: Name: NameFull: Brooks JM – PersonEntity: Name: NameFull: Bernard BB – PersonEntity: Name: NameFull: MacDonald A – PersonEntity: Name: NameFull: MacAdam N – PersonEntity: Name: NameFull: Campbell C – PersonEntity: Name: NameFull: Fowler M – PersonEntity: Name: NameFull: Hubert CRJ IsPartOfRelationships: – BibEntity: Dates: – D: 07 M: 10 Text: 2025 Oct 07 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 2165-0497 Numbering: – Type: volume Value: 13 – Type: issue Value: 10 Titles: – TitleFull: Microbiology spectrum Type: main |
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