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SPIRE2005

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In our case, we look for the substrings (with their arcs) ... Local edit distance O(nm) [Smith Waterman 1981] Normalized LCS O(mnlogn) [Arslan Pevzner 2001] ... – PowerPoint PPT presentation

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Title: SPIRE2005


1


Normalized Similarity of RNA Sequences
Rolf Backofen Danny Hermelin Gad M. LandauOren
Weimann
2
RNA sequences
3
RNA sequences
C G
C G
G C
C
A U
U A
C G
A
G
U
A
G
U
C
G
U
A
G
U
A
C
C
A
C
A
G
U
U
G
C
G
G
4
LCS of Strings
S1
C
G
U
A
G
U
A
C
C
A
C
A
G
U
G
U
G
G
C
S2
A
G
C
A
G
C
C
U
C
G
G
G
C
G
G
A
A
U
U
Global LCS
Hirschberg 1977
5
LCS of RNA sequences
Left arc match
Right arc match
RNA Global LCS Klein
1998
6
Global Similarity - LCS
7
Local Similarity Normalized LCS
  • Report the most similar substring pair according
    to some scoring scheme.
  • In our case, we look for the substrings
    (with their arcs) that maximize
  • Can be viewed as measure of the density of the
    matches.

8
Local Similarity in Strings
  • Local edit distance O(nm) Smith Waterman 1981
  • Normalized LCS O(mnlogn) Arslan Pevzner 2001
  • Normalized LCS for sparse matrices O(rLloglogn)
  • Efraty Landau 2004

9
Our Result
  • A novel local similarity metric for comparing RNA
    sequences.
  • An time algorithm for computing
    this metric.
  • As fast as the global algorithm (in contrast to
    the case of strings).

10
Definitions
  • A chain is a sequence of matches that is strictly
    increasing in rows and columns.
  • The length of a chain from (i,j) to match (i,j)
    is i-ij-j.
  • A k-chain(i,j) is the shortest chain of k
    matches starting from (i,j).
  • The normalized value of k-chain(i,j) is k
    divided by its length. ( )

11
  • General idea - Construct (k1)-chain(i,j) by
    concatenating (i,j) to k-chain(i,j) .

a b c a d e c f h c
a
g
g
b
f
h
e
c
g
g
g
f
d
e
f
12
Decomposing k-Chains
13
Decomposing k-Chains (non arc match)
Best (k-1)-Chain
14
Decomposing k-Chains (mismatch)
15
Decomposing k-Chains (right arc match)
Best k-Chain
16
Decomposing k-Chains (left arc match)
17
Decomposing k-Chains (left arc match I)
18
Example 2-Chain
19
Decomposing k-Chains (left arc match II)
20
Decomposing k-Chains (left arc match II)
k lcs
Best (k-lcs)-Chain
21
Decomposing k-Chains (left arc match III)
k lcs
22
Example 3-Chain
23
The Algorithm (Given R1,R2)
  • Run Kleins algorithm to get LCS of every arc in
    R1 with every arc in R2.
  • For k1,2,,n
  • Construct all k-chains from
  • bottom right to top left using DP.
  • Report best k-chain.
  • Total of - as fast as
    global LCS

24
The DP
25
Muchas Gracias por la atencion
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