Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors
The COVID-19 pandemic demands assimilation of all biomedical knowledge to decode mechanisms of pathogenesis. Despite the recent renaissance in neural networks, a platform for the real-time synthesis of the exponentially growing biomedical literature and deep omics insights is unavailable. Here, we present the nferX platform for dynamic inference from 45 quadrillion+ possible conceptual associations from unstructured text and triangulation with insights from Single Cell RNA-sequencing, bulk RNAseq and proteomics from diverse tissue types. A hypothesis-free profiling of ACE2 suggests tongue keratinocytes, olfactory epithelial cells, airway club cells and respiratory ciliated cells as potential reservoirs of the SARS-CoV-2 receptor. We find the gut as the putative hotspot of COVID-19, where a maturation correlated transcriptional signature is shared in small intestine enterocytes among coronavirus receptors(ACE2, DPP4, ANPEP). A holistic data science platform triangulating insights from structured and unstructured data holds potential for accelerating the generation of impactful biological insights and hypotheses.
All data used in this manuscript were obtained from published and freely available sources online. A complete list of these can be found in Supplementary File 1.
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No external funding was received for this work.
- Mone Zaidi, Icahn School of Medicine at Mount Sinai, United States
- Received: April 18, 2020
- Accepted: May 27, 2020
- Accepted Manuscript published: May 28, 2020 (version 1)
- Version of Record published: July 20, 2020 (version 2)
© 2020, Venkatakrishnan et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Key Technological Projects of Guangdong Province grant 2018B030335001.
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