__Bioinformatics Algorithms__

C-113 HN, 1:10 PM - 2:25 PM

Office Hours: Mon 2:30 PM - 4:30 PM

Saad Mneimneh

**Book**

An Introduction to Bioinformatics Algorithms, by Jones and Pevzner

**Lectures**

Lecture 1: Intro to Bio and CS, DNA copying, a flavor of sequencing problems,
pages 14-19, and chapter 3

Lecture 2: Algorithmic paradigms, greedy and brute force coin change, recursive Tower of Hanoi, pages 20-33

Lecture 3: Sorring, Fibonacci, Big O notation, pages 33-40

Lecture 4: Dynamic programming coin change, pages 41-50, 148-152

Lecture 5: Big-O vs small-o, dynamic programming vs divide and conquer, continue with dynamic programming, sequence alignment, pages 177-178

Lectures 6: Local alignment, overlap alignment

Lecture 7: Scoring matrices, pages 178-185, more general gap functions, see my notes here

Lecture 8: Multiple alignment, star alignment pages 186-193

Lecture 9: Space and time improvements, pages 227-240, but book has slightly different presentation than lecture, see my notes here

Lecture 10: Gene prediction, rectangle chaining, and spliced alignment, pages 200-206

Lecture 11: Genetic mapping, pages 83-96

Lecture 12: Motif Finding, pages 91-111

Lecture 13: Genome rearrangement, sorting by reversal, pages 125-135

Lecture 14: Gene sequencing, shortest superstring, Hampath and a greedy algorithm, pages 262-268

Lecture 15: Sequencing by hybridization SBH, Euler path, pages 268-274

Lecture 16: Protein sequencing, k-similarity and spectral alignment, pages 280-299

Lecture 17: Hash tables, applications to database search and repeat finding, pages 311-318

Lecture 18: Suffix trees and pattern matching, pages 320-324

Lecture 19: More applications of suffix trees, finding maximal repeats, all pair suffix-prefix problem

Lecture 20: Hidden Markov Models, Viterbi algorithm

Lecture 21: Maximum parsimony

Lecture 22: Hierarchical clustering and k-means

Lecture 23: Perfect phylogeny

Lecture 24: Distance based trees

**Homework (almost biweekly)**

Homework 0, summarize chapter 3 of the book, due Thu 2/2/2017

Homework 1, due Thu 2/9/2017 Solution

Homework 2, due Thu 2/23/2017 Solution

Homework 3, due Thu 3/9/2017, Solution

Homework 4, due Mon 3/3/2017, Solution

**Test** will be on Mon March 27 in class.

Homework 5, due Thu 4/27/2017, Solution

Homework 6, due last day of class, Solution

**Grading policy**

Homework 30%

Midterm 20%

Project/Report 10%

Final 40%