Author: Brandon Malone; Boris Simovski; Clement Moline; Jun Cheng; Marius Gheorghe; Hugues Fontenelle; Ioannis Vardaxis; Simen Tennoe; Jenny-Ann Malmberg; Richard Stratford; Trevor Clancy
Title: Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2: toward universal blueprints for vaccine designs Document date: 2020_4_21
ID: cm30gyd8_99
Snippet: Specifically, we collect all genotypes observed at least once across all regions; we assign an index g to each genotype, and we call the total number of unique genotypes as G. Second, we specify a prior distribution over genotypes. We use a symmetric Dirichlet distribution with concentration parameter of 0.5 because this distribution is uninformative in an information theoretic sense and does not reflect strong prior beliefs that any particular g.....
Document: Specifically, we collect all genotypes observed at least once across all regions; we assign an index g to each genotype, and we call the total number of unique genotypes as G. Second, we specify a prior distribution over genotypes. We use a symmetric Dirichlet distribution with concentration parameter of 0.5 because this distribution is uninformative in an information theoretic sense and does not reflect strong prior beliefs that any particular genotypes are more likely to appear in any specific region. For each region, we then calculate a posterior distribution over genotypes as a Dirichlet distribution as follows.
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