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Article

Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases

1
Integrated Program in Quantitative Biology, University of California San Francisco, San Francisco, CA 94143, USA
2
Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA
3
KBR, NASA Ames Research Center, Moffett Field, CA 94035, USA
4
NASA Postdoctoral Program, Universities Space Research Association (USRA), Mountain View, CA 94043, USA
5
Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA 94143, USA
6
Department of Pediatrics, University of California San Francisco, San Francisco, CA 94143, USA
7
Weill Institute for Neuroscience, Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
*
Authors to whom correspondence should be addressed.
Life 2021, 11(1), 42; https://doi.org/10.3390/life11010042
Received: 10 December 2020 / Revised: 1 January 2021 / Accepted: 4 January 2021 / Published: 12 January 2021
(This article belongs to the Special Issue Space Life Sciences)
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. View Full-Text
Keywords: spaceflight; knowledge graph; transcriptomics spaceflight; knowledge graph; transcriptomics
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MDPI and ACS Style

Nelson, C.A.; Acuna, A.U.; Paul, A.M.; Scott, R.T.; Butte, A.J.; Cekanaviciute, E.; Baranzini, S.E.; Costes, S.V. Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases. Life 2021, 11, 42. https://doi.org/10.3390/life11010042

AMA Style

Nelson CA, Acuna AU, Paul AM, Scott RT, Butte AJ, Cekanaviciute E, Baranzini SE, Costes SV. Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases. Life. 2021; 11(1):42. https://doi.org/10.3390/life11010042

Chicago/Turabian Style

Nelson, Charlotte A.; Acuna, Ana U.; Paul, Amber M.; Scott, Ryan T.; Butte, Atul J.; Cekanaviciute, Egle; Baranzini, Sergio E.; Costes, Sylvain V. 2021. "Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases" Life 11, no. 1: 42. https://doi.org/10.3390/life11010042

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