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A machine learning approach to identify key epigenetic transcripts for ageing research in human blood (Epitage).

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Title: A machine learning approach to identify key epigenetic transcripts for ageing research in human blood (Epitage).
Authors: Benazzi Maia T; Laboratory of Regulation of Gene Expression, IRCCS AOM San Martino, Genova, Italy. a00s@a00s.com., Pfeffer U; Laboratory of Regulation of Gene Expression, IRCCS AOM San Martino, Genova, Italy.
Source: Biogerontology [Biogerontology] 2026 Jul 22; Vol. 27 (4). Date of Electronic Publication: 2026 Jul 22.
Publication Type: Journal Article
Journal Info: Publisher: Kluwer Academic Country of Publication: Netherlands NLM ID: 100930043 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-6768 (Electronic) Linking ISSN: 13895729 NLM ISO Abbreviation: Biogerontology Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Benazzi+Maia+T%22">Benazzi Maia T</searchLink>; Laboratory of Regulation of Gene Expression, IRCCS AOM San Martino, Genova, Italy. a00s@a00s.com.<br /><searchLink fieldCode="AU" term="%22Pfeffer+U%22">Pfeffer U</searchLink>; Laboratory of Regulation of Gene Expression, IRCCS AOM San Martino, Genova, Italy.
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  Data: <searchLink fieldCode="JN" term="%22100930043%22">Biogerontology</searchLink> [Biogerontology] 2026 Jul 22; Vol. 27 (4). <i>Date of Electronic Publication: </i>2026 Jul 22.
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      – Type: doi
        Value: 10.1007/s10522-026-10473-6
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      – Code: eng
        Text: English
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      – TitleFull: A machine learning approach to identify key epigenetic transcripts for ageing research in human blood (Epitage).
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            NameFull: Benazzi Maia T
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            NameFull: Pfeffer U
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            – D: 22
              M: 07
              Text: 2026 Jul 22
              Type: published
              Y: 2026
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              Value: 27
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              Value: 4
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