Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.
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What you need before starting this Dynamic Programming: Applications In Machine Learning and Genomics course:
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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.
Difficulty Level
Intermediate
Some foundational knowledge required
Subject Category
Computer Science, Math, Biology & Life Sciences
Part of our Computer Science, Math, Biology & Life Sciences curriculum
Course Language
English
All materials in English
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Comprehensive Program
Professional training from $150
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