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Computational protocol to identify shared transcriptional risks and mutually beneficial compounds between diseases.
Gao, Hua; Zhang, Mao; Baylis, Richard A; Wang, Fudi; Björkegren, Johan L M; Kovacic, Jason J; Ruusalepp, Arno; Leeper, Nicholas J.
Afiliación
  • Gao H; Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA. Electronic address: ghbore@gmail.com.
  • Zhang M; Stanford Cardiovascular Institute, Stanford, CA 94305, USA.
  • Baylis RA; Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA; Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco, CA 94143, USA.
  • Wang F; Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA.
  • Björkegren JLM; Department of Medicine, Karolinska Institute, Huddinge, Sweden; Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
  • Kovacic JJ; Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia; St. Vincent's Clinical School, University of NSW, Sydney, NSW, Australia.
  • Ruusalepp A; Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia.
  • Leeper NJ; Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford, CA 94305, USA; Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, U
STAR Protoc ; 5(1): 102883, 2024 Mar 15.
Article en En | MEDLINE | ID: mdl-38354084
ABSTRACT
The accumulation of omics and biobank resources allows for a genome-wide understanding of the shared pathologic mechanisms between diseases and for strategies to identify drugs that could be repurposed as novel treatments. Here, we present a computational protocol, implemented as a Snakemake workflow, to identify shared transcriptional processes and screen compounds that could result in mutual benefit. This protocol also includes a description of a pharmacovigilance study designed to validate the effect of compounds using electronic health records. For complete details on the use and execution of this protocol, please refer to Gao et al.1 and Baylis et al.2.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 Problema de salud: 1_sistemas_informacao_saude Asunto principal: Flujo de Trabajo Tipo de estudio: Etiology_studies / Guideline / Risk_factors_studies Idioma: En Revista: STAR Protoc Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 Problema de salud: 1_sistemas_informacao_saude Asunto principal: Flujo de Trabajo Tipo de estudio: Etiology_studies / Guideline / Risk_factors_studies Idioma: En Revista: STAR Protoc Año: 2024 Tipo del documento: Article
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