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Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases.
Nelson, Charlotte A; Acuna, Ana Uriarte; Paul, Amber M; Scott, Ryan T; Butte, Atul J; Cekanaviciute, Egle; Baranzini, Sergio E; Costes, Sylvain V.
Afiliação
  • Nelson CA; Integrated Program in Quantitative Biology, University of California San Francisco, San Francisco, CA 94143, USA.
  • Acuna AU; Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA.
  • Paul AM; KBR, NASA Ames Research Center, Moffett Field, CA 94035, USA.
  • Scott RT; Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA.
  • Butte AJ; NASA Postdoctoral Program, Universities Space Research Association (USRA), Mountain View, CA 94043, USA.
  • Cekanaviciute E; Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA.
  • Baranzini SE; KBR, NASA Ames Research Center, Moffett Field, CA 94035, USA.
  • Costes SV; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA 94143, USA.
Life (Basel) ; 11(1)2021 Jan 12.
Article em En | MEDLINE | ID: mdl-33445483
ABSTRACT
There has long been an interest in understanding how the hazards from spaceflight may trigger or exacerbate human diseases. With the goal of advancing our knowledge on physiological changes during space travel, NASA GeneLab provides an open-source repository of multi-omics data from real and simulated spaceflight studies. Alone, this data enables identification of biological changes during spaceflight, but cannot infer how that may impact an astronaut at the phenotypic level. To bridge this gap, Scalable Precision Medicine Oriented Knowledge Engine (SPOKE), a heterogeneous knowledge graph connecting biological and clinical data from over 30 databases, was used in combination with GeneLab transcriptomic data from six studies. This integration identified critical symptoms and physiological changes incurred during spaceflight.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article