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## PowerPoint Slideshow about ' Sequence Alignment' - roary-brennan

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Dynamic Programming

- Optimization problems: find the best decision one after another
- Subproblems are not independent
- Subproblems share subsubproblems
- Solve subproblem, save its answer in a table

Genomics & Computational Biology

Four Steps of DP

- Characterize the structure of an optimal solution
- Recursively define the value of an optimal solution
- Compute the value of an optimal solution in a bottom-up fashion
- Construct an optimal solution from computed information

Genomics & Computational Biology

Sequence Alignment

Sequence 1: G A A T T C A G T T A

Sequence 2: G G A T C G A

Genomics & Computational Biology

Align or insert gap

G A A T T C A G T T A

| | | | | |

G G A _ T C _ G _ _ A

G _ A A T T C A G T T A

| | | | | |

G G _ A _ T C _ G _ _ A

Genomics & Computational Biology

Three Steps of SA

- Initialization: gap penalty
- Scoring: matrix fill
- Alignment: trace back

Genomics & Computational Biology

Step 1: Initialization

Genomics & Computational Biology

Step 2: Scoring

- A = a1a2…an, B = b1b2…bm
- Sij : score at (i,j)
- s(aibj) : matching score between ai andbj
- w : gap penalty

figure source

Genomics & Computational Biology

Step 2: Scoring

Genomics & Computational Biology

Step 3: Trace back

Genomics & Computational Biology

Step 3: Trace back

G A A T T C A G T T A

G G A _ T C _ G _ _ A

G A A T T C A G T T A

G G A T _ C _ G _ _ A

Genomics & Computational Biology

Excercise

- Match: +2
- Mismatch: -1
- Gap: -2
G C A T C C G

G A T C G

G A T C G

G A T C G

Genomics & Computational Biology

Global & Local alignment

- Global: Needlman-Wunsch Algorithm
- Local: Smith-Waterman Algorithm

From Mount Bioinformatics Chap 3

Genomics & Computational Biology

References

- Sequence alignment with Java applet
- http://linneus20.ethz.ch:8080/5_4_5.html

Genomics & Computational Biology

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