Machine learning prediction of prime editing efficiency across diverse chromatin contexts.
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| Title: | Machine learning prediction of prime editing efficiency across diverse chromatin contexts. |
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| Authors: | Mathis N; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., Allam A; Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland., Tálas A; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., Kissling L; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., Benvenuto E; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., Schmidheini L; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.; Institute of Molecular Health Sciences, ETH Zurich, Zurich, Switzerland., Schep R; Oncode Institute, Netherlands Cancer Institute, Amsterdam, the Netherlands.; Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, the Netherlands., Damodharan T; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., Balázs Z; Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland., Janjuha S; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., Ioannidi EI; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., Böck D; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland., van Steensel B; Oncode Institute, Netherlands Cancer Institute, Amsterdam, the Netherlands.; Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, the Netherlands., Krauthammer M; Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland., Schwank G; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland. schwank@pharma.uzh.ch. |
| Source: | Nature biotechnology [Nat Biotechnol] 2025 May; Vol. 43 (5), pp. 712-719. Date of Electronic Publication: 2024 Jun 21. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature America Publishing Country of Publication: United States NLM ID: 9604648 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1546-1696 (Electronic) Linking ISSN: 10870156 NLM ISO Abbreviation: Nat Biotechnol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 38907037 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Machine learning prediction of prime editing efficiency across diverse chromatin contexts. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Mathis+N%22">Mathis N</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Allam+A%22">Allam A</searchLink>; Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Tálas+A%22">Tálas A</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Kissling+L%22">Kissling L</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Benvenuto+E%22">Benvenuto E</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Schmidheini+L%22">Schmidheini L</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.; Institute of Molecular Health Sciences, ETH Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Schep+R%22">Schep R</searchLink>; Oncode Institute, Netherlands Cancer Institute, Amsterdam, the Netherlands.; Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Damodharan+T%22">Damodharan T</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Balázs+Z%22">Balázs Z</searchLink>; Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Janjuha+S%22">Janjuha S</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Ioannidi+EI%22">Ioannidi EI</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Böck+D%22">Böck D</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22van+Steensel+B%22">van Steensel B</searchLink>; Oncode Institute, Netherlands Cancer Institute, Amsterdam, the Netherlands.; Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Krauthammer+M%22">Krauthammer M</searchLink>; Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.<br /><searchLink fieldCode="AU" term="%22Schwank+G%22">Schwank G</searchLink>; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland. schwank@pharma.uzh.ch. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%229604648%22">Nature biotechnology</searchLink> [Nat Biotechnol] 2025 May; Vol. 43 (5), pp. 712-719. <i>Date of Electronic Publication: </i>2024 Jun 21. – 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="%22Nature+America+Publishing%22">Nature America Publishing </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>9604648 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1546-1696 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2210870156%22">10870156 </searchLink><i>NLM ISO Abbreviation: </i>Nat Biotechnol <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=38907037 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41587-024-02268-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 712 Titles: – TitleFull: Machine learning prediction of prime editing efficiency across diverse chromatin contexts. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mathis N – PersonEntity: Name: NameFull: Allam A – PersonEntity: Name: NameFull: Tálas A – PersonEntity: Name: NameFull: Kissling L – PersonEntity: Name: NameFull: Benvenuto E – PersonEntity: Name: NameFull: Schmidheini L – PersonEntity: Name: NameFull: Schep R – PersonEntity: Name: NameFull: Damodharan T – PersonEntity: Name: NameFull: Balázs Z – PersonEntity: Name: NameFull: Janjuha S – PersonEntity: Name: NameFull: Ioannidi EI – PersonEntity: Name: NameFull: Böck D – PersonEntity: Name: NameFull: van Steensel B – PersonEntity: Name: NameFull: Krauthammer M – PersonEntity: Name: NameFull: Schwank G IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: 2025 May Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 1546-1696 Numbering: – Type: volume Value: 43 – Type: issue Value: 5 Titles: – TitleFull: Nature biotechnology Type: main |
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