BIOMETRICS. Module Code: CA641 Week 11- Pairwise Sequence Alignment. Outline. Why should one do sequence comparison ? Dynamic programming alignment algorithms global alignment (Needleman- Wunsch ) local alignment (Smith-Waterman ) Heuristic alignment algorithms : FASTA , BLAST
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
BIOMETRICS
Module Code: CA641
Week 11- Pairwise Sequence Alignment
Acknowledgement: this presentation was created following Prof. LiviuCiortuz, “Computer Science” Faculty, “Al. I. Cuza” University, Iasi, Romania: http://profs.info.uaic.ro/~ciortuz/
a non-human species - extensively studied to understand particular biological phenomena
used to research human disease
Escherichia coli
Drosophila melanogaster
Zea mays
Laboratory mice
Image source: http://en.wikipedia.org/wiki/Model_organism
where xi, yi are from the alphabet Alf = {A, C, G, T}, what is their similarity?
where:
Simple
Used in genome alignments
Examples from this presentation use d = -8.
F(0,0) =0, F(i,0)=-id, F(0,j) = -jd, for i=1..n, j=1..m
There are three ways in which the best score F(i,j) of an alignment up to xi, yj could be obtained:
F(i,j)= max
Fill in the matrix F from top left to bottom right.
-d
-d
F(0,0) =0, F(i,0)= F(0,j) = 0, for i=1..n, j=1..m
There are three ways in which the best score F(i,j) of an alignment up to xi, yj could be obtained:
F(i,j)= max
Fill in the matrix F from top left to bottom right.
For the local alignment algorithm to work,
long matches between unrelated sequences will have the high score, just based on their length, and a true local alignment would be masked by a longer but incorrect one.
GCCGAGCTAG
CCTAGCAAG