High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.
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| Title: | High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV. |
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| Authors: | Liao H; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Conwill A; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Light-Maka I; Max Planck Institute for Infection Biology; Berlin 10117, Germany.; Charité-Universitätsmedizin Berlin, Berlin 10117, Germany., Fenk M; Max Planck Institute for Infection Biology; Berlin 10117, Germany.; Humboldt-Universität zu Berlin, Faculty of Life Sciences, Berlin, Germany., Mitchell AH; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Qu EB; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Torrillo P; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Baker JS; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA., Key FM; Max Planck Institute for Infection Biology; Berlin 10117, Germany., Lieberman TD; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA.; Ragon Institute of MGH, MIT, and Harvard; Cambridge, MA 02139, USA. |
| Source: | BioRxiv : the preprint server for biology [bioRxiv] 2025 Sep 29. Date of Electronic Publication: 2025 Sep 29. |
| Publication Type: | Journal Article; Preprint |
| Journal Info: | Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41256411 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Liao+H%22">Liao H</searchLink>; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.<br /><searchLink fieldCode="AU" term="%22Conwill+A%22">Conwill A</searchLink>; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.<br /><searchLink fieldCode="AU" term="%22Light-Maka+I%22">Light-Maka I</searchLink>; Max Planck Institute for Infection Biology; Berlin 10117, Germany.; Charité-Universitätsmedizin Berlin, Berlin 10117, Germany.<br /><searchLink fieldCode="AU" term="%22Fenk+M%22">Fenk M</searchLink>; Max Planck Institute for Infection Biology; Berlin 10117, Germany.; Humboldt-Universität zu Berlin, Faculty of Life Sciences, Berlin, Germany.<br /><searchLink fieldCode="AU" term="%22Mitchell+AH%22">Mitchell AH</searchLink>; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.<br /><searchLink fieldCode="AU" term="%22Qu+EB%22">Qu EB</searchLink>; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.<br /><searchLink fieldCode="AU" term="%22Torrillo+P%22">Torrillo P</searchLink>; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.<br /><searchLink fieldCode="AU" term="%22Baker+JS%22">Baker JS</searchLink>; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.<br /><searchLink fieldCode="AU" term="%22Key+FM%22">Key FM</searchLink>; Max Planck Institute for Infection Biology; Berlin 10117, Germany.<br /><searchLink fieldCode="AU" term="%22Lieberman+TD%22">Lieberman TD</searchLink>; Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA.; Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA.; Ragon Institute of MGH, MIT, and Harvard; Cambridge, MA 02139, USA. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101680187%22">BioRxiv : the preprint server for biology</searchLink> [bioRxiv] 2025 Sep 29. <i>Date of Electronic Publication: </i>2025 Sep 29. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Preprint – Name: TitleSource Label: Journal Info Group: Src Data: <i>Country of Publication: </i>United States <i>NLM ID: </i>101680187 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2692-8205 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2226928205%22">26928205 </searchLink><i>NLM ISO Abbreviation: </i>bioRxiv <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41256411 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1101/2025.09.26.678787 Languages: – Code: eng Text: English Titles: – TitleFull: High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liao H – PersonEntity: Name: NameFull: Conwill A – PersonEntity: Name: NameFull: Light-Maka I – PersonEntity: Name: NameFull: Fenk M – PersonEntity: Name: NameFull: Mitchell AH – PersonEntity: Name: NameFull: Qu EB – PersonEntity: Name: NameFull: Torrillo P – PersonEntity: Name: NameFull: Baker JS – PersonEntity: Name: NameFull: Key FM – PersonEntity: Name: NameFull: Lieberman TD IsPartOfRelationships: – BibEntity: Dates: – D: 29 M: 09 Text: 2025 Sep 29 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 2692-8205 Titles: – TitleFull: BioRxiv : the preprint server for biology Type: main |
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