Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

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 p...

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Bibliographic Details
Main Authors: AJ Venkatakrishnan, Arjun Puranik, Akash Anand, David Zemmour, Xiang Yao, Xiaoying Wu, Ramakrishna Chilaka, Dariusz K Murakowski, Kristopher Standish, Bharathwaj Raghunathan, Tyler Wagner, Enrique Garcia-Rivera, Hugo Solomon, Abhinav Garg, Rakesh Barve, Anuli Anyanwu-Ofili, Najat Khan, Venky Soundararajan
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2020-05-01
Series:eLife
Subjects:
COVID-19
SARS-CoV-2
single cell RNA-seq
natural language processing
artificial intelligence
machine learning
Online Access:https://elifesciences.org/articles/58040

Internet

https://elifesciences.org/articles/58040

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