A meta-analysis of RNA-Seq studies to identify novel genes that regulate aging.

Bairakdar, Mohamad D; Tewari, Ambuj; Truttmann, Matthias C

Bairakdar, Mohamad D; Tewari, Ambuj; Truttmann, Matthias C.

Afiliación

Bairakdar MD; Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.
Tewari A; Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA; Department of Statistics, University of Michigan, Ann Arbor, MI 48109, USA.
Truttmann MC; Department of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, MI, 48109, USA; Geriatrics Center, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: mtruttma@med.umich.edu.

Exp Gerontol ; 173: 112107, 2023 03.

Article en En | MEDLINE | ID: mdl-36731807

Asunto(s)

Proteínas de Caenorhabditis elegans; Caenorhabditis elegans; Animales; Caenorhabditis elegans/metabolismo; Proteínas de Caenorhabditis elegans/genética; Proteínas de Caenorhabditis elegans/metabolismo; RNA-Seq; Envejecimiento/genética; Longevidad/genética

Palabras clave

Aging; C. elegans; Longevity; Machine learning; RNAseq; Reproducibility

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Caenorhabditis elegans / Proteínas de Caenorhabditis elegans Tipo de estudio: Systematic_reviews Límite: Animals Idioma: En Año: 2023 Tipo del documento: Article

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