M.M. Dalkilic, PhD
Monday, September 08, 2008
Class V
Indiana University, Bloomington, IN
Sequence Homology
1
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
Outline
New Programming Assignment and homework will be
posted today
New Reading Posted on Website
Readings [R] Chaps 5
Most Important Aspect of Bioinformatics
—
homology search
through sequence similarity (cont’d)
Sequence Alignment (Theoretical)
Sequence Alignment (Practical) FASTA and BLAST
Quick detour first
2
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
Brief Review of Probability
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
3
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
4
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
5
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
6
We know from the previous slides that
P
is a measure over a Boolean algebra.
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
7
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
8
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
9
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
10
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
11
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
12
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
13
Odds or (subjective probability) play a significant role in bioinformatics
We either have “odds for (or on)” or “odds against”
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
14
Increasing information about an event can lead to a change in probability
—
since, for some, a probability is a degree of belief…Bayesians.
Review cont’d
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
15
FASTA and BLAST
—
Dot Plots
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
16
Simplest means of comparing two sequences
Visualization is easy to understand
—
can be the basis for
explaining both FASTA and BLAST
A Dot plot is simply a rectangular grid whose leftmost
column and bottom row are sequences. A box is checked if,
for cell
i
,
j
,
the symbols match
i
units from the bottom

to

top
and
j
units from left

to

right
Dot Plots
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
17
A Dot plot is simply a rectangular grid whose leftmost
column and bottom row are sequences. A box is checked if,
for cell
i
,
j
,
the symbols match
i
units from the bottom

to

top
and
j
units from left

to

right
Dot Plots
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
18
A Dot plot is simply a rectangular grid whose leftmost
column and bottom row are sequences. A box is checked if,
for cell
i
,
j
,
the symbols match
i
units from the bottom

to

top
and
j
units from left

to

right
Scoring Matrix
Noise or possible
motifs separated by
gaps
Dot Plots
Sequence Similiarty (Computation) M.M. Dalkilic, PhD
SoI Indiana University, Bloomington, IN 2008 ©
19
Learn to read plots

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