BPS 4104 Chapter Notes - Chapter 13: Substitution Model, Molecular Phylogenetics, Markov Chain

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Chapter 13: Molecular Phylogenetics Part One
Substitution Models
-reflect our understanding of how molecular sequences change over time
-theoretical foundation for computing genetic distance in distance based
phylogenetic methods
-three types of molecular sequences: nucleotide, amino acid, codon
-three types of substitution models: nucleotide based, amino acid based, and codon
based
Nucleotide Based Substitution Models
-typically expressed as a transition probability matrix in the framework of a Markov
chain
-a value in a transition probability matrix shows probability of a nucleotide or
amino acid in the leftmost column staying the same or changing into another one
over a time interval
-different substitution models differ in the transition probability matrix
-frequently used substitution models: JC69, K80,F81/TN84, HKY85, TN93, GTR
-these models differ by two sets of parameters: frequency parameters and
rate parameters
-simplest substitution model is JC69:
-assumes that frequency parameters are all equal to 0.25
-# of frequency parameters we need to estimate from sequence data is 0
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Document Summary

Reflect our understanding of how molecular sequences change over time. Theoretical foundation for computing genetic distance in distance based phylogenetic methods. Three types of molecular sequences: nucleotide, amino acid, codon. Three types of substitution models: nucleotide based, amino acid based, and codon based. Typically expressed as a transition probability matrix in the framework of a markov chain. A value in a transition probability matrix shows probability of a nucleotide or amino acid in the leftmost column staying the same or changing into another one over a time interval. Different substitution models differ in the transition probability matrix. Frequently used substitution models: jc69, k80,f81/tn84, hky85, tn93, gtr. These models differ by two sets of parameters: frequency parameters and rate parameters. Assumes that frequency parameters are all equal to 0. 25. # of frequency parameters we need to estimate from sequence data is 0. Also assumes that substitutions between any two nucleotides have same rate (one rate model)

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