Ab initio =from the beginning in strictest sense uses first principles, not information about other protein structures In practice, all methods rely on empirical observations

Algorithms for detecting structure similarity Dynamic Programming works on 1D strings- reduce problem to this cant accommodate topological changes example: Secondary Structure Alignment Program(SSAP) 3D Comparison/Clustering

For a molecular simulation or model you need 1. a representation of the protein 2. An energy function 3. a search algorithm or optimizer

Review of protein structure hierarchy Nonpolar, Hydrophobic R-grou Primary structure Glycin (Gly, G) Aa,A≌ alina (VaL V. Leucine(Lou, L) Isoleucine{,非 MAAAAAAGPEMVRGQVE 20 amino acids Phenylalanine(Ph,月

Review of markov HMM Models for dna Markov Models for splice sites Hidden Markov models looking under the hood The Viterbi algorithm Real World HMMs

Markov Hidden markov models for dna Markov Models for splice sites Hidden Markov models looking under the hood The Viterbi algorithm Real World HMMs

Review of DNA Seq. Comparison/Alignment Target frequencies and mismatch penalties Eukaryotic gene structure Comparative genomics applications Pipmaker(2 species comparison) Phylogenetic Shadowing(many species) Intro to DNA sequence motifs

The Language of genomics CDNAS, ESTS. BACS Alus. etc Dideoxy Method Shotgun Sequencing The 'shotgun coverage equation(Poisson) Flavors of blast BLASTIPNXJ, TBLASTINXI Statistics of High Scoring Segments

Outline FASTA, Blast searching, Smith-Waterman Psi-Blast Review of Genomic DNA structure Substitution patterns and mutation rates Synonymous and non-Synonymous substitutions Jukes-Cantor Model Kimura's Two-Parameter Model

Outline Multiple Sequence AlignmentCarillo-& Lipman, Clustal(W) Position-Specific Scoring Matrices(PSSM) Information content, Shannon entropy Sequence logos Hidden Markov Models Other approaches: Genetic algorithms, expectation maximization, MEME, Gibbs sampler