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Articles 1 - 2 of 2
Full-Text Articles in Genetics and Genomics
Integrate Structural Analysis, Isoform Diversity, And Interferon-Inductive Propensity Of Ace2 To Predict Sars-Cov2 Susceptibility In Vertebrates, Eric R. Sang, Yun Tian, Yuanying Gong, Laura C. Miller, Yongming Sang
Integrate Structural Analysis, Isoform Diversity, And Interferon-Inductive Propensity Of Ace2 To Predict Sars-Cov2 Susceptibility In Vertebrates, Eric R. Sang, Yun Tian, Yuanying Gong, Laura C. Miller, Yongming Sang
Agricultural and Environmental Sciences Faculty Research
The current new coronavirus disease (COVID-19) has caused globally over 0.4/6 million confirmed deaths/infected cases across more than 200 countries. As the etiological coronavirus (a.k.a. SARS-CoV2) may putatively have a bat origin, our understanding about its intermediate reservoir between bats and humans, especially its tropism in wild and domestic animals are mostly unknown. This constitutes major concerns in public health for the current pandemics and potential zoonosis. Previous reports using structural analysis of the viral spike protein (S) binding its cell receptor of angiotensin-converting enzyme 2 (ACE2), indicate a broad potential of SARS-CoV2 susceptibility in wild and particularly domestic animals. …
Machine Learning With Digital Signal Processing For Rapid And Accurate Alignment-Free Genome Analysis: From Methodological Design To A Covid-19 Case Study, Gurjit Singh Randhawa
Machine Learning With Digital Signal Processing For Rapid And Accurate Alignment-Free Genome Analysis: From Methodological Design To A Covid-19 Case Study, Gurjit Singh Randhawa
Electronic Thesis and Dissertation Repository
In the field of bioinformatics, taxonomic classification is the scientific practice of identifying, naming, and grouping of organisms based on their similarities and differences. The problem of taxonomic classification is of immense importance considering that nearly 86% of existing species on Earth and 91% of marine species remain unclassified. Due to the magnitude of the datasets, the need exists for an approach and software tool that is scalable enough to handle large datasets and can be used for rapid sequence comparison and analysis. We propose ML-DSP, a stand-alone alignment-free software tool that uses Machine Learning and Digital Signal Processing to …