Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases
| Autor: | Sylvain V. Costes, Charlotte A. Nelson, Ryan T. Scott, Egle Cekanaviciute, Ana Uriarte Acuna, Amber M. Paul, Sergio E. Baranzini, Atul J. Butte |
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| Rok vydání: | 2020 |
| Předmět: |
spaceflight
knowledge graph transcriptomics Computer science Network embedding Paleontology Signs and symptoms Precision medicine Spaceflight Data science General Biochemistry Genetics and Molecular Biology Article law.invention Good Health and Well Being Knowledge graph Space and Planetary Science law lcsh:Q Identification (biology) lcsh:Science Ecology Evolution Behavior and Systematics |
| Zdroj: | Life Life; Volume 11; Issue 1; Pages: 42 Life (Basel, Switzerland), vol 11, iss 1 Life, Vol 11, Iss 42, p 42 (2021) |
| ISSN: | 2075-1729 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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