791_cb_lecture4

791_cb_lecture4 - 7.91 / 7.36 / BE.490 Lecture #4 Mar. 4,...

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7.91 / 7.36 / BE.490 Lecture #4 Mar. 4, 2004 Markov & Hidden Markov Models for DNA Sequence Analysis Chris Burge
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Organization of Topics Model Dependence Lecture Object Structure Weight Matrix Model Hidden Markov Model Independence 3/2 Local 3/4 Dependence Energy Model, Covariation Model Non-local Dependence 3/9
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Markov & Hidden Markov Models for DNA • Hidden Markov Models - looking under the hood See Ch. 4 of Mount • Markov Models for splice sites • The Viterbi Algorithm • Real World HMMs
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Review of DNA Motif Modeling & Discovery • Information Content of a Motif See Ch. 4 of Mount • WMMs for splice sites • The Motif Finding/Discovery Problem • The Gibbs Sampler • Motif Modeling - Beyond Weight Matrices
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Information Content of a DNA/RNA Motif -3 -2 -1 1 2 3 4 5 6 f k = freq. of nt k at position Shannon Entropy H ( G f ) =− f log 2 ( f k k ) (bits) k Information/position ) = 2 + f log 2 ( f ) = f log 2 ( 1 f k ) (bits) k k k k k 4 G f G f I ( ) = 2 H ( Motif containing m bits of info. will occur approximately once per 2 m bases of random sequence
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Variables Affecting Motif Finding gcggaagagggcactagcccatgtgagagggcaaggacca± atctttctcttaaaaataacataattcagggccaggatgt± gtcacgagctttatcctacagatgatgaatgcaaatcagc± taaaagataatatcgaccctagcgtggcgggcaaggtgct± L = avg. sequence length gtagattcgggtaccgttcataaaagtacgggaatttcgg± tatacttttaggtcgttatgttaggcgagggcaaaagtca± ctctgccgattcggcgagtgatcgaagagggcaatgcctc± aggatggggaaaatatgagaccaggggagggccacactgc± N = no. of sequences acacgtctagggctgtgaaatctctgccgggctaacagac± gtgtcgatgttgagaacgtaggcgccgaggccaacgctga± atgcaccgccattagtccggttccaagagggcaactttgt± ctgcgggcggcccagtgcgcaacgcacagggcaaggttta± I = info. content of motif tgtgttgggcggttctgaccacatgcgagggcaacctccc± gtcgcctaccctggcaattgtaaaacgacggcaatgttcg± cgtattaatgataaagaggggggtaggaggtcaactcttc± aatgcttataacataggagtagagtagtgggtaaactacg± W = motif width tctgaaccttctttatgcgaagacgcgagggcaatcggga±
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791_cb_lecture4 - 7.91 / 7.36 / BE.490 Lecture #4 Mar. 4,...

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