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The GENDULF algorithm: mining transcriptomics to uncover modifier genes for monogenic diseases.
Auslander, Noam; Ramos, Daniel M; Zelaya, Ivette; Karathia, Hiren; Crawford, Thomas O; Schäffer, Alejandro A; Sumner, Charlotte J; Ruppin, Eytan.
Affiliation
  • Auslander N; Cancer Data Science Laboratory (CDSL), National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Ramos DM; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
  • Zelaya I; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Karathia H; Interdepartmental Program in Bioinformatics, University of California Los Angeles, Los Angeles, CA, USA.
  • Crawford TO; Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, MD, USA.
  • Schäffer AA; Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Sumner CJ; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Ruppin E; Cancer Data Science Laboratory (CDSL), National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Mol Syst Biol ; 16(12): e9701, 2020 12.
Article in En | MEDLINE | ID: mdl-33438800
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Disease / Data Mining / Transcriptome / Genes, Modifier Type of study: Prognostic_studies Limits: Humans Language: En Journal: Mol Syst Biol Journal subject: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Year: 2020 Document type: Article Affiliation country: Country of publication:
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Disease / Data Mining / Transcriptome / Genes, Modifier Type of study: Prognostic_studies Limits: Humans Language: En Journal: Mol Syst Biol Journal subject: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Year: 2020 Document type: Article Affiliation country: Country of publication: