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Logistics
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Lecture Overview
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Introduction to Epigenomics
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Three types of Epigenomic Modifications
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Q1: Non-standard modifications
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Q2: Epigenetic inheritance
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Q3: Developmental memory establishment
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Diversity of Histone modifications
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Methylation Bisulfite and DNase Profiling
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Antibodies, ChIP-Seq, data generation projects, raw data
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Read mapping: Hashing, Suffix Trees, Burrows-Wheeler Transform
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Quality Control, Cross-correlation, Peak calling, IDR similar to FDR
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Discovery and characterization of chromatin states
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HMM Foundations, Generating, Parsing, Decoding, Learning
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Two Sets of HMM parameters: Emissions, Transitions
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Example 2-state HMM, observations, scoring, inference
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Viterbi algorithm: Find best parse π*= argmaxπPx,π
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Posterior Decoding: Most likely state πiover all paths
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Summary
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into the world of epigenomics and Hidden Markov Models (HMMs) in this comprehensive lecture. Explore the three types of epigenomic modifications, including histone modifications, DNA methylation, and chromatin accessibility. Learn about diverse histone modifications, methylation profiling techniques, and data generation methods like ChIP-Seq. Discover read mapping algorithms, quality control processes, and peak calling techniques. Delve into the foundations of HMMs, including their parameters, parsing, and decoding methods. Understand the Viterbi algorithm for finding the best parse and posterior decoding for determining the most likely state. Gain insights into non-standard modifications, epigenetic inheritance, and developmental memory establishment through engaging Q&A segments.

Epigenomics and Hidden Markov Models in Computational Biology - Lecture 5

Manolis Kellis
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