The Breakpoint Graph 1 5- 2- 4 3. The Breakpoint Graph Augment with 0 = n+1 6 1 5- 2- 4 3 0.

Slides:



Advertisements
Similar presentations
Great Theoretical Ideas in Computer Science for Some.
Advertisements

Coloring Warm-Up. A graph is 2-colorable iff it has no odd length cycles 1: If G has an odd-length cycle then G is not 2- colorable Proof: Let v 0, …,
A Simpler 1.5-Approximation Algorithm for Sorting by Transpositions Tzvika Hartman Weizmann Institute.
Sorting by reversals Bogdan Pasaniuc Dept. of Computer Science & Engineering.
Lecture 5 Graph Theory. Graphs Graphs are the most useful model with computer science such as logical design, formal languages, communication network,
De Bruijn sequences Rotating drum problem:
Max Flow Problem Given network N=(V,A), two nodes s,t of V, and capacities on the arcs: uij is the capacity on arc (i,j). Find non-negative flow fij for.
Convex drawing chapter 5 Ingeborg Groeneweg. Summery What is convex drawing What is convex drawing Some definitions Some definitions Testing convexity.
Comp 122, Spring 2004 Greedy Algorithms. greedy - 2 Lin / Devi Comp 122, Fall 2003 Overview  Like dynamic programming, used to solve optimization problems.
Introduction to Graph Theory Lecture 11: Eulerian and Hamiltonian Graphs.
Lecture 16: DFS, DAG, and Strongly Connected Components Shang-Hua Teng.
Chapter 9 Connectivity 连通度. 9.1 Connectivity Consider the following graphs:  G 1 : Deleting any edge makes it disconnected.  G 2 : Cannot be disconnected.
Finding a Maximum Matching in Non-Bipartite Graphs Alicia Thilani Singham Goodwin /22/2013.
Section 2.1 Euler Cycles Vocabulary CYCLE – a sequence of consecutively linked edges (x 1,x2),(x2,x3),…,(x n-1,x n ) whose starting vertex is the ending.
Minimum Spanning Trees Definition Algorithms –Prim –Kruskal Proofs of correctness.
Network Optimization Problems: Models and Algorithms This handout: Minimum Spanning Tree Problem.
What is the next line of the proof? a). Let G be a graph with k vertices. b). Assume the theorem holds for all graphs with k+1 vertices. c). Let G be a.
Sorting Signed Permutations By Reversals (The Hannenhalli – Pevzner Theory) Seminar in Bioinformatics – ©Shai Lubliner.
Graphs and Trees This handout: Trees Minimum Spanning Tree Problem.
Of Mice and Men Learning from genome reversal findings Genome Rearrangements in Mammalian Evolution: Lessons From Human and Mouse Genomes and Transforming.
Is the following graph Hamiltonian- connected from vertex v? a). Yes b). No c). I have absolutely no idea v.
1 Michal Ozery-Flato and Ron Shamir 2 The Genomic Sorting Problem HOW?
Chapter 4: Straight Line Drawing Ronald Kieft. Contents Introduction Algorithm 1: Shift Method Algorithm 2: Realizer Method Other parts of chapter 4 Questions?
5. Lecture WS 2003/04Bioinformatics III1 Genome Rearrangements Compare to other areas in bioinformatics we still know very little about the rearrangement.
1 Sorting by Transpositions Based on the First Increasing Substring Concept Advisor: Professor R.C.T. Lee Speaker: Ming-Chiang Chen.
3/24/03Tucker, Section 4.31 Tucker, Applied Combinatorics, Sec. 4.3, prepared by Jo E-M Bipartite GraphMatching Some Definitions X-Matching Maximal Matching.
A Linear-Time Algorithm for Computing Inversion Distance between signed Permutations with an experimental Study David Bader, Bernard Moret, Mi Yan Presented.
Efficient Data Structures and a New Randomized Approach for Sorting Signed Permutations by Reversals Haim Kaplan and Elad Verbin.
A Simplified View of DCJ-Indel Distance Phillip Compeau A Simplified View of DCJ- Indel Distance Phillip Compeau University of California-San Diego Department.
 Jim has six children.  Chris fights with Bob,Faye, and Eve all the time; Eve fights (besides with Chris) with Al and Di all the time; and Al and Bob.
Genome Rearrangements …and YOU!! Presented by: Kevin Gaittens.
Genome Rearrangements Tseng Chiu Ting Sept. 24, 2004.
1 A Simpler 1.5- Approximation Algorithm for Sorting by Transpositions Combinatorial Pattern Matching (CPM) 2003 Authors: T. Hartman & R. Shamir Speaker:
A Simpler 1.5-Approximation Algorithm for sorting by transposition Tzvika Hartman.
Genome Rearrangements Unoriented Blocks. Quick Review Looking at evolutionary change through reversals Find the shortest possible series of reversals.
Chap. 7 Genome Rearrangements Introduction to Computational Molecular Biology Chap ~
Chap. 7 Genome Rearrangements Introduction to Computational Molecular Biology Chapter 7.1~7.2.4.
& Problem Solving.  You will be able to use the converse of a theorem to construct parallel lines.  You will be able to use theorems to find the measures.
and 6.855J March 6, 2003 Maximum Flows 2. 2 Network Reliability u Communication Network u What is the maximum number of arc disjoint paths from.
Section 3.5 Properties of Parallel Lines. Transversal  Is a line that intersects two or more coplanar lines at different points.  Angles formed:  Corresponding.
Proving Lines are Parallel Unit IC Day 12. Do now: Complete the statements If two parallel lines are cut by a transversal, then Corresponding angles are.
Homework - hints Problem 1. Node weights  Edge weights
Genome Rearrangement By Ghada Badr Part I.
Genome Rearrangements. Turnip vs Cabbage: Look and Taste Different Although cabbages and turnips share a recent common ancestor, they look and taste different.
Tzvika Hartman Elad Verbin Bar Ilan University Tel Aviv University
Graphs Definition: a graph is an abstract representation of a set of objects where some pairs of the objects are connected by links. The interconnected.
Senior Project Board Implementation of the Solution to the Conjugacy Problem in Thompson’s Group F by Nabil Hossain Advisers: James Belk & Robert McGrail.
Maryam Pourebadi Kent State University April 2016.
Hex: a Game of Connecting Faces. Player 1 Player 2 Players take turns placing blue chips (player 1) and red chips (player 2). Player 1 plays first. Player.
De Bruijn sequences 陳柏澍 Novembers Each of the segments is one of two types, denoted by 0 and 1. Any four consecutive segments uniquely determine.
4.2 Transversals and Parallel Lines Pgs. 26, 28, 30.
3.3 Parallel Lines and Transversals
Conservation of Combinatorial Structures in Evolution Scenarios
Graph theory Definitions Trees, cycles, directed graphs.
Greedy Algorithms / Minimum Spanning Tree Yin Tat Lee
Proof and Perpendicular Lines
Spanning Trees Discrete Mathematics.
Greedy (Approximation) Algorithms and Genome Rearrangements
Lecture 3: Genome Rearrangements and Duplications
CSCI2950-C Lecture 4 Genome Rearrangements
Greedy Algorithms And Genome Rearrangements
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 7th ed., by Kenneth H.
3-6: Prove Theorems about Perpendicular Lines
Max Flow Min Cut, Bipartite Matching Yin Tat Lee
Characterizing Matrices with Consecutive Ones Property
MNL appears to be what type of angle?
FanChang Hao, Melvin Zhang, and Hon Wai Leong Review for TCBB
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 8th ed., by Kenneth H.
Simple Graphs: Connectedness, Trees
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 7th ed., by Kenneth H.
Presentation transcript:

The Breakpoint Graph

The Breakpoint Graph Augment with 0 = n

The Breakpoint Graph Augment with 0 = n+1 Vertices 2i, 2i-1 for each i

The Breakpoint Graph Augment with 0 = n+1 Vertices 2i, 2i-1 for each i Blue edges between adjacent vertices

The Breakpoint Graph Augment with 0 = n+1 Vertices 2i, 2i-1 for each i Blue edges between adjacent vertices Red edges between consecutive labels 2i,2i

into n+1 trivial cycles Sort a given breakpoint graph

Sort a given breakpoint graph Conclusion: We want to increase number of cycles into n+1 trivial cycles

Def:A reversal acts on two blue edges cutting them and re-connecting them

A reversal can either Act on two cycles, joining them (bad!!)

A reversal can either Act on one cycle, changing it (profitless)

A reversal can either Act on one cycle, splitting it (good move)

Basic Theorem Where d=#reversals needed (reversal distance), and c=#cycles. Proof: Every reversal changes c by at most 1. (Bafna, Pevzner 93)

Where d=#reversals needed (reversal distance), and c=#cycles. Proof: Every reversal changes c by at most 1. Alternative formulation: where b=#breakpoints, and c ignores short cycles Basic Theorem (Bafna, Pevzner 93)

Right-to-Right Left-to-Left Left-to-Right Right-to-Left Red edges can be : Oriented { Unoriented { Oriented Edges

Right-to-Right Left-to-Left Left-to-Right Right-to-Left Red edges can be : Oriented { Unoriented { Def:This reversal acts on the red edge Oriented Edges

Right-to-Right Left-to-Left Left-to-Right Right-to-Left Red edges can be : Oriented { Unoriented { Def:This reversal acts on the red edge Oriented Edges Thm: A reversal acting on a red edge is good the edge is oriented

Def: Two red edges are said to be overlapping if they span intersecting intervals which do not contain one another. Overlapping Edges

Def: Two red edges are said to be overlapping if they span intersecting intervals which do not contain one another The lines intersect

Thm:A reversal acting on a red edge flips the orientation of all edges overlapping it, leaving other orientations unchanged Overlapping Edges Def: Two red edges are said to be overlapping if they span intersecting intervals which do not contain one another The lines intersect

Thm:if e,f,g overlap each other, then after applying a reversal that acts on e, f and g do not overlap Overlapping Edges Def: Two red edges are said to be overlapping if they span intersecting intervals which do not contain one another The lines intersect

Overlap Graph Nodes correspond to red edges. Two nodes are connected by an arc if they overlap

Overlap Graph Def:Unoriented connected components in the overlap graph - all nodes correspond to oriented edges. Nodes correspond to red edges. Two nodes are connected by an arc if they overlap

Overlap Graph Def:Unoriented connected components in the overlap graph - all nodes correspond to oriented edges. Cannot be solved in only good moves Nodes correspond to red edges. Two nodes are connected by an arc if they overlap

Dealing with Unoriented Components A profitless move on an oriented edge, making its component to oriented

Dealing with Unoriented Components A profitless move on an oriented edge, making its component to oriented or: A bad move (reversal) joining cycles from different unoriented components, thus merging them flipping the orientation of many components on the way

Merging Unoriented Components

Hurdles Def:Hurdle - an unoriented connected component which is consecutive along the cycle

Hurdles Def:Hurdle - an unoriented connected component which is consecutive along the cycle Thm: ( Hannenhalli, Pevzner 95) Proof: A hurdle is destroyed by a profitless move, or at most two are destroyed (merged) by a bad move.

Hurdles Def:Hurdle - an unoriented connected component which is consecutive along the cycle Thm: ( Hannenhalli, Pevzner 95) Proof: A hurdle is destroyed by a profitless move, or at most two are destroyed (merged) by a bad move. Thm: