https://www.selleckchem.com/products/n6f11.html
Under these circumstances, one way to optimize HAM detection is to integrate all relevant information in a coherent model. Bayesian inference offers a principled approach to achieve this. We present a new Bayesian regression model for the detection of HAMs that integrates a sparsity-inducing prior, epitope predictions, and phylogenetic bias assessment, and that yields easily interpretable quantitative information on HAM candidates. The model predicts experimentally confirmed HAMs as having high posterior probabilities, and it performs wel
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