Manolis Kellis
@manoliskellis1·24.9K subscribers·255 videos
MIT CompBio Lecture 02 - Dynamic Programming (Fall'19)
Posted
September 10, 2019
Views
12,695
Likes
173
Comments
9
Engagement
1.43%
September 10, 2019
12,695
173
9
1.43%
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1:19:28Now PlayingMIT Computational Biology: Genomes, Networks, Evolution, Health
Prof. Manolis Kellis
Full playlist with all videos in order is here
All slides from Fall 2019 are here
Outline for this lecture:
1. Introduction to sequence alignment
- Comparative genomics and molecular evolution
- From Bio to CS: Problem formulation
- Why it’s hard: Exponential number of alignments
2. Introduction to principles of dynamic programming
- Computing Fibonacci numbers: Top-down vs. bottom-up
- Repeated sub-problems, ordering compute, table lookup
- DP recipe: (1) Parameterization, (2) sub-problem space, (3) traversal order, (4) recursion formula, (5) trace-back
3. DP for sequence alignment
- Additive score, building up a solution from smaller parts
- Prefix matrix: finite subproblems, exponential paths
- Duality: each entry=prefix alignment score, path=aligmnt
4. Advanced topics: Dynamic Programming variants
- Linear-time bounded DP(heuristic). Better than O(n2)?
- Linear-space DP: Four-Russians algorithm. Total time?
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