Lecture 11

Learning objectives

After this class, you should be able to:

1. Given two sequences of letters, their similarity matrix, and the gap penalty, determine the best global alignment for the two sequences using the Needleman-Wunsch algorithm.
2. Analyze the time complexity of the above algorithm.
3. Given a similar problem, give an algorithm, based on dynamic programming, to solve it, and analyze its time complexity.

Reading assignment

1. Needleman-Wunsch algorithm slides.

Exercises and review questions

• Questions on current lecture's material
  1. (Post your answer on the discussion board. You need not show the score and traceback matrices there.) Give an example of two amino-acid sequences of length at least 4 and compute their best sequence alignment with the BLOSUM62 substitution matrix (for similarity) using the Needleman-Wunsch algorithm.
  2. Instead of filling the score matrix by rows, can we fill it by columns? (That is, fill column i before filling column i+1.)

• Questions on next lecture's material
  1. The Needleman-Wunsch algorithm computes the scores for prefixes. Can you solve the same problem by computing the suffixes? Gove the recurrence for that.