Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data.
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| Title: | Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data. |
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| Authors: | Norris R; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK., Jones J; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK., Mancini E; School of Life Sciences, University of Sussex, Brighton, UK., Chevassut T; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK., Simoes FA; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK., Pepper C; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK., Pepper A; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK., Mitchell S; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK. S.A.Mitchell@bsms.ac.uk. |
| Source: | Blood cancer journal [Blood Cancer J] 2024 Jul 04; Vol. 14 (1), pp. 105. Date of Electronic Publication: 2024 Jul 04. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101568469 Publication Model: Electronic Cited Medium: Internet ISSN: 2044-5385 (Electronic) Linking ISSN: 20445385 NLM ISO Abbreviation: Blood Cancer J Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 38965209 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Norris+R%22">Norris R</searchLink>; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK.<br /><searchLink fieldCode="AU" term="%22Jones+J%22">Jones J</searchLink>; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK.<br /><searchLink fieldCode="AU" term="%22Mancini+E%22">Mancini E</searchLink>; School of Life Sciences, University of Sussex, Brighton, UK.<br /><searchLink fieldCode="AU" term="%22Chevassut+T%22">Chevassut T</searchLink>; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK.<br /><searchLink fieldCode="AU" term="%22Simoes+FA%22">Simoes FA</searchLink>; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK.<br /><searchLink fieldCode="AU" term="%22Pepper+C%22">Pepper C</searchLink>; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK.<br /><searchLink fieldCode="AU" term="%22Pepper+A%22">Pepper A</searchLink>; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK.<br /><searchLink fieldCode="AU" term="%22Mitchell+S%22">Mitchell S</searchLink>; Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, UK. S.A.Mitchell@bsms.ac.uk. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101568469%22">Blood cancer journal</searchLink> [Blood Cancer J] 2024 Jul 04; Vol. 14 (1), pp. 105. <i>Date of Electronic Publication: </i>2024 Jul 04. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Research Support, Non-U.S. Gov't – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Pub%2E+Group%22">Nature Pub. Group </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101568469 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2044-5385 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220445385%22">20445385 </searchLink><i>NLM ISO Abbreviation: </i>Blood Cancer J <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=38965209 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41408-024-01090-y Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 105 Titles: – TitleFull: Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Norris R – PersonEntity: Name: NameFull: Jones J – PersonEntity: Name: NameFull: Mancini E – PersonEntity: Name: NameFull: Chevassut T – PersonEntity: Name: NameFull: Simoes FA – PersonEntity: Name: NameFull: Pepper C – PersonEntity: Name: NameFull: Pepper A – PersonEntity: Name: NameFull: Mitchell S IsPartOfRelationships: – BibEntity: Dates: – D: 04 M: 07 Text: 2024 Jul 04 Type: published Y: 2024 Identifiers: – Type: issn-electronic Value: 2044-5385 Numbering: – Type: volume Value: 14 – Type: issue Value: 1 Titles: – TitleFull: Blood cancer journal Type: main |
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