Dynamic Programming - Applications In Machine Learning and Genomics

Overview

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 Dynamic Programming - Applications In Machine Learning and Genomics Certificate, part of the Algorithms and Data Structures MicroMasters Program from EdX in partnership with University of California, San Diego - UC San DiegoX, 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.

What you'll learn

• Dynamic programming and how it applies to basic string comparison algorithms

• Sequence alignment, including how to generalize dynamic programming algorithms to handle different cases

• Hidden markov models

• How to find the most likely sequence of events given a collection of outcomes and limited information

• Machine learning in sequence alignment