Introduction	
                                                                                                                               
Squence analysis                                                                                                               
     a. Sequence alignment intro     
       i. The concept of an algorithm                             
        ii. Complexity                                            
        iii. Strategies for algorithm design                         
     b. Motif finding                                             
        i. Exhaustive search and greedy algorithms                
        ii. is it real? stat review                                 
     c. Scalable sequence alignment                                 
        i. dynamic programming                                    
        ii. local and global alignments, PAM and BLOSUM, gaps     
        iii. BLAST and alignment statistics                       
                                                                    
                                                                    
MIDTERM I                                                            
                                                                    
Genomic Scale Analysis                                               
     a. Comparative methods                                         
        i. multiple alignment                                        
        ii. phyogenitics, Ka/Ks                                   
     b. Gene prediction                                             
        i. statistical methods                                    
        ii. regression, neural nets                                 
        iii. HMMs                                                    
     c. Gene expression                                             
        methods & Applications                                      
        i. Clustering (k-means and heirarchical                   
        ii. interpretation of clusters (GO, etc.)                 
        iii. experimental design of gene expression experiments     
     d. Proteomics                                                  
        i. protein identification                                    
                                                                                                                               
Structure                                                                                                                      
        a. RNA                                                                                                                    
        b. Protein