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Phylogenetic Models for Motif Detection

Phylogenetic Models for Motif Detection. Pradipta Ray ( joint work advised by Eric Xing ). What. Repeating, roughly conserved genetic sequence of biological sequence “Pure” pattern matching techniques give you a large number of false matches : low precision Best modelled as semi supervised.

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Phylogenetic Models for Motif Detection

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  1. Phylogenetic Models for Motif Detection Pradipta Ray ( joint work advised by Eric Xing ) Student Research Symposium, LTI, CMU, 2005

  2. What • Repeating, roughly conserved genetic sequence of biological sequence • “Pure” pattern matching techniques give you a large number of false matches : low precision • Best modelled as semi supervised Student Research Symposium, LTI, CMU, 2005

  3. The Problem Definition • Motif formalism • Positional Weight Matrix • Sequence of 4-nomials • Supervised : Simple MLE for multinomial Student Research Symposium, LTI, CMU, 2005

  4. Traditional Approaches • Unsupervised: • Gibbs Sampling • Expectation Maximization • De novo detection Student Research Symposium, LTI, CMU, 2005

  5. Knowledge is power • Motifs are conserved sites • Given aligned sequences, we may choose suitable regions Student Research Symposium, LTI, CMU, 2005

  6. A look at motif evolution • Work by Krietman et al • Functional evolution : granularity of theevolving unit is larger than the nucleotide Student Research Symposium, LTI, CMU, 2005

  7. Phylogenetic Trees ( T , L , P , M ) T = ( V, E ) = Tree topology L : E  REdge lengths P : Multinomial parameters for initial draw M : CTMM parameters Student Research Symposium, LTI, CMU, 2005

  8. Phylogenetic HMM C1 A G G A A P1 Student Research Symposium, LTI, CMU, 2005

  9. The mixture of trees model Student Research Symposium, LTI, CMU, 2005

  10. A G G A A Student Research Symposium, LTI, CMU, 2005

  11. Student Research Symposium, LTI, CMU, 2005

  12. Learning • Learning the evolutionary trees • Learning the annotation trees Student Research Symposium, LTI, CMU, 2005

  13. Inferencing the Tree ? ? ? ? Student Research Symposium, LTI, CMU, 2005

  14. Usage • Framework for answering questions about evolution of macro-entities • A specific and highly significant case would be that of motif finding Student Research Symposium, LTI, CMU, 2005

  15. Conclusion • Currently being implemented • To be tested with data from the Drosophilae species Student Research Symposium, LTI, CMU, 2005

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