Article

Non-parametric Bayesian density estimation for biological sequence space with applications to pre-mRNA splicing and the karyotypic diversity of human cancer

2020-11-27

Abstract excerpt

Density estimation in sequence space is a fundamental problem in machine learning that is of great importance in computational biology. Due to the discrete nature and large dimensionality of sequence space, how best to estimate such probability distributions from a sample of observed sequences remains unclear. One common strategy for addressing this problem is to estimate the probability distribution using maximum...

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Literature Corpus work: c08bc311-8ab6-5338-8995-226f1c933ba0
DOI: 10.1101/2020.11.25.399253

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