1. Needleman_Wunsch algorithm of global alignment Chap. 6 Higgs and Attwood

2. The accumulation of substitutions in two sequences descending from a common ancestor Q. Why evolutionary models? A.To infer d(A,B) from D(A,B) B.Through an evolutionary (probabilistic model) Note: D is not linear in time (see above) and is not Additive D 12  D 01 +D 02

3. BASIC CONCEPTS UP TO THIS POINT: HOMOLOGY, ORTHOLOGY, PARALOGY

4. Algorithms (exact/heuristic) Trade off: Time vs. memory Insertion-sort algorithm Traveling salesman algorithm (exhaustion, scale as N!) Greedy local algorithm (frustration) Pairwise sequence alignment (gap cost functions) O(N  ) NP complete Dynamic programming Local /global alignments

5. Insertion sort and traveling salesman O(N 2 )O(N!)

6. Gap cost function Scoring alignments: Score=∑ i S(a i,b i )-∑ g W(l)

7. PAM250 matrix calculated by Tayloe and Thornton (1992), upper triangle: number of observed substitutions A ij. Diagonal and lower triangle: log-odds score S ij =10Log 10 R ij

8. H(i,j)= H(i-1,j-1)+S(a i,b j ) diagonal H(i-1,j) - g vertical H(i,j-1) - g vertical

9. Alignment of the Brca1 protein sequences from the same region of the gene as in fig. 3.1