Learning to align with differentiable dynamic programming | Michiel Stock | JuliaCon2021
This talk was presented as part of JuliaCon2021
Abstract:
The alignment of two or more biological sequences is one of the main workhorses in bioinformatics because it can quantify similarity and reveal conserved patterns. We provided a differential version of the two most popular algorithms for sequence alignment: the Needleman–Wunsch and Smith-Waterman algorithms. Using ChainRulesCore.jl, the gradients can be used directly in combination with bioinformatics and machine learning libraries.
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