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Intro to Probabilistic Models PSSMs

Intro to Probabilistic Models PSSMs. Computational Genomics, Lecture 6b Partially based on slides by Metsada Pasmanik-Chor. Biological Motives.

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Intro to Probabilistic Models PSSMs

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  1. Intro to Probabilistic ModelsPSSMs Computational Genomics, Lecture 6b Partially based on slides by Metsada Pasmanik-Chor

  2. Biological Motives A large number of biological units with common functions tend to exhibit similarities at the sequence level. These include very short “motives”, such as gene splice sites, DNA regulatory binding sites, recognized by transcription factors (proteins that bind to the promoter and control gene expression), microRNAs, and all the way to protein families. Often it is desirable to model such motives, to enable searching for new ones. Probabilistic models are very useful.Today we deal with PSSM - the simplest.

  3. Promoter…

  4. Regulation of Genes Transcription Factor (Protein) RNA polymerase (Protein) DNA Gene Regulatory Element www.cs.washington.edu/homes/tompa/papers/binding.ppt

  5. Regulation of Genes Transcription Factor (Protein) RNA polymerase DNA Regulatory Element Gene

  6. Regulation of Genes New protein RNA polymerase Transcription Factor DNA Regulatory Element Gene

  7. Motif Logo Position: • Motifs can mutate on less important bases. • The five motifs at top right have mutations in position 3 and 5. • Representations called motif logos illustrate the conserved regions of a motif. 1234567 TGGGGGA TGAGAGA TGGGGGA TGAGAGA TGAGGGA http://weblogo.berkeley.edu http://fold.stanford.edu/eblocks/acsearch.html

  8. Example: Calmodulin-Binding Motif (calcium-binding proteins)

  9. PSSM Starting Point • A gap-less MSA of known instances of a given motif. Representing the motif by either: • Consensus. • Position Specific Scoring Matrix (PSSM). Consider now a specific “motives server”, called Consite.

  10. Sequence logos: Visualizing PSSMs

  11. Sequence logos: Visualizing PSSMs (2)

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