Lecture 12

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 Hirschberg's 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. Hirschberg algorithm slides.
2. CLR: page 387.
3. CLR: Chapter 15, page 391.

Exercises and review questions

• Questions on current lecture's material
  1. Show all steps in Hirschberg's algorithm for the strings given in the lecture slides.

• Questions on next lecture's material
  1. (Post your solution on the discussion board) Give examples of two sequences of at least four elements each, and identify their longest common subsequence.
  2. Give an efficient algorithm for computing the n th term of a Fibonacci sequence using memoization.