UCSanDiegoX: Dynamic Programming: Applications In Machine Learning and Genomics
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Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.
About this course
If you look at two genes that serve the same purpose in two different species, how can you rigorously compare these genes in order to see how they have evolved away from each other?
In the first part of the course, part of the Algorithms and Data Structures MicroMasters program, we will see how the dynamic programming paradigm can be used to solve a variety of different questions related to pairwise and multiple string comparison in order to discover evolutionary histories.
In the second part of the course, we will see how a powerful machine learning approach, using a Hidden Markov Model, can dig deeper and find relationships between less obviously related sequences, such as areas of the rapidly mutating HIV genome.
At a Glance:
Institution: UCSanDiegoX
Subject: Computer Science
Level: Intermediate
Prerequisites:
Basic knowledge of:
at least one programming language: loops, arrays, stacks, recursion.
mathematics: proof by induction, proof by contradiction.
Language: English
Video Transcript: English
Associated programs:
MicroMasters® Program in Algorithms and Data Structures
Associated skills:Hidden Markov Model, Data Structures, Genomics, Machine Learning, Algorithms, Dynamic Programming
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