Table of Contents18.417 - Lecture 3Review - Dynamic Programming Why dynamic programming From Global to Local alignments 0. Setting up the scoring matrix 1. Allowing gaps in s 2. Allowing gaps in t 3. Allowing mismatches 4. Choosing optimal paths 5. Rewarding matches From Global to Local alignments Semi-Global Motivation Ignoring starting gaps Ignoring trailing gaps Using the new scoring scheme Semi-global alignments Semi-Global Alignment From Global to Local alignments Intro to Local Alignments Global Alignment Local Alignment Local Alignment issues From Global to Local alignments Motivation for affine gap penalty Additional Matrices Update rules Simplified rules General Gap Penalty From Global to Local alignments Dynamic Programming Versatility DP Algorithm Variations What’s next |
Authors: Manolis Kamvysselis and Bonnie
Berger
Email: manoli@mit.edu and bab@mit.edu Home Page: http://theory.lcs.mit.edu/~bab/01-18.417-home.html Other information:
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