#28 Space-efficient variable-order Markov models with Fabio Cunial - a podcast by Roman Cheplyaka

This time you’ll hear from Fabio Cunial on the topic of Markov models and
space-efficient data structures. First we recall what a Markov model is and
why variable-order Markov models are an improvement over the standard,
fixed-order models. Next we discuss the various data structures and indexes
that allowed Fabio and his collaborators to represent these models in a very
small space while still keeping the queries efficient. Burrows-Wheeler
transform, suffix trees and arrays, tries and suffix link trees, and more!

Links:

• The preprint: A framework for space-efficient variable-order Markov models


• The book: Genome-Scale Algorithm Design


• The GitHub repo

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