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Dynamic Programming: Applications In Machine Learning and Genomics

Dynamic Programming: Applications In Machine Learning and Genomics

Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.
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Course Website
www.edx.org
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Description

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.


Pricing:
Free
Level:
Intermediate
Duration:
4 weeks, 8h-10h/week
Educator:
Pavel Pevzner
Organization:
The University of California, San Diego
Submitted by:
Coursearena
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