Efficient Merging and Construction of Evolutionary Trees Andrzej Lingas,Hans Olsson, and Anna Ostlin Journal of Algorithms 2001 Reporter: Jian-Fu Dong.

Slides:



Advertisements
Similar presentations
Routing and Congestion Problems in General Networks Presented by Jun Zou CAS 744.
Advertisements

Chapter 11 Limitations of Algorithm Power Copyright © 2007 Pearson Addison-Wesley. All rights reserved.
WSPD Applications.
22nd International Symposium on Graph Drawing
1 LP Duality Lecture 13: Feb Min-Max Theorems In bipartite graph, Maximum matching = Minimum Vertex Cover In every graph, Maximum Flow = Minimum.
Orthogonal Drawing Kees Visser. Overview  Introduction  Orthogonal representation  Flow network  Bend optimal drawing.
O(N 1.5 ) divide-and-conquer technique for Minimum Spanning Tree problem Step 1: Divide the graph into  N sub-graph by clustering. Step 2: Solve each.
AVL Trees1 Part-F2 AVL Trees v z. AVL Trees2 AVL Tree Definition (§ 9.2) AVL trees are balanced. An AVL Tree is a binary search tree such that.
Sorting Comparison-based algorithm review –You should know most of the algorithms –We will concentrate on their analyses –Special emphasis: Heapsort Lower.
Rooted Routing Using Structural Decompositions Jiao Tong University Shanghai, China June 17, 2013.
Advanced Topics in Algorithms and Data Structures Lecture 7.1, page 1 An overview of lecture 7 An optimal parallel algorithm for the 2D convex hull problem,
GENE TREES Abhita Chugh. Phylogenetic tree Evolutionary tree showing the relationship among various entities that are believed to have a common ancestor.
Heapsort By: Steven Huang. What is a Heapsort? Heapsort is a comparison-based sorting algorithm to create a sorted array (or list) Part of the selection.
Advanced Topics in Algorithms and Data Structures 1 Rooting a tree For doing any tree computation, we need to know the parent p ( v ) for each node v.
June 3, 2015Windows Scheduling Problems for Broadcast System 1 Amotz Bar-Noy, and Richard E. Ladner Presented by Qiaosheng Shi.
Sorting Heapsort Quick review of basic sorting methods Lower bounds for comparison-based methods Non-comparison based sorting.
Efficient algorithms for Steiner Tree Problem Jie Meng.
Chapter 11 Limitations of Algorithm Power Copyright © 2007 Pearson Addison-Wesley. All rights reserved.
Phylogenetic Tree Construction and Related Problems Bioinformatics.
Packing Element-Disjoint Steiner Trees Mohammad R. Salavatipour Department of Computing Science University of Alberta Joint with Joseph Cheriyan Department.
1 Efficiently Mining Frequent Trees in a Forest Mohammed J. Zaki.
Advanced Topics in Algorithms and Data Structures 1 An example.
CPSC 335 BTrees Dr. Marina Gavrilova Computer Science University of Calgary Canada.
Chapter 11 Limitations of Algorithm Power. Lower Bounds Lower bound: an estimate on a minimum amount of work needed to solve a given problem Examples:
Computational Complexity Polynomial time O(n k ) input size n, k constant Tractable problems solvable in polynomial time(Opposite Intractable) Ex: sorting,
Trees Chapter 15 Data Structures and Problem Solving with C++: Walls and Mirrors, Carrano and Henry, © 2013.
CS Data Structures Chapter 15 Trees Mehmet H Gunes
Descendent Subtrees Comparison of Phylogenetic Trees with Applications to Co-evolutionary Classifications in Bacterial Genome Yaw-Ling Lin 1 Tsan-Sheng.
Binary Trees. Binary Tree Finite (possibly empty) collection of elements A nonempty binary tree has a root element The remaining elements (if any) are.
The Fast Optimal Voltage Partitioning Algorithm For Peak Power Density Minimization Jia Wang, Shiyan Hu Department of Electrical and Computer Engineering.
Analysis techniques Pasi Fränti Ordo O(g) – Upper Bound f(n) ≤ c∙g(n) Omega  (g)– Lower Bound f(n) ≥ c∙g(n) Theta Θ(g)– Exact limit: c 1 ∙g(n)
Sorting Lower Bounds Amihood Amir Bar-Ilan University 2014.
1 Lower Bounds Lower bound: an estimate on a minimum amount of work needed to solve a given problem Examples: b number of comparisons needed to find the.
Discrete Structures Lecture 12: Trees Ji Yanyan United International College Thanks to Professor Michael Hvidsten.
 Rooted tree and binary tree  Theorem 5.19: A full binary tree with t leaves contains i=t-1 internal vertices.
5.5.2 M inimum spanning trees  Definition 24: A minimum spanning tree in a connected weighted graph is a spanning tree that has the smallest possible.
Line Transversals to Disjoint Balls (Joint with C. Borcea, O. Cheong, X. Goaoc, A. Holmsen) Sylvain Petitjean LORIA, Vegas team O. Schwarzkopf.
Sorting Conclusions David Kauchak cs302 Spring 2013.
MA/CSSE 473 Day 21 AVL Tree Maximum height 2-3 Trees Student questions?
5.5.3 Rooted tree and binary tree  Definition 25: A directed graph is a directed tree if the graph is a tree in the underlying undirected graph.  Definition.
1 Deploying Wireless Sensors to Achieve Both Coverage and Connectivity Xiaole Bai*, Santosh Kumar*, Dong Xuan*, Ziqiu Yun +, Ten H. Lai* * Computer Science.
KAIS T Deploying Wireless Sensors to Achieve Both Coverage and Connectivity Xiaole Bai, Santosh Kumar, Dong Xuan, Ziqiu Yun and Ten H.Lai MobiHoc 2006.
Chapter 18: Searching and Sorting Algorithms. Objectives In this chapter, you will: Learn the various search algorithms Implement sequential and binary.
Union Find ADT Data type for disjoint sets: makeSet(x): Given an element x create a singleton set that contains only this element. Return a locator/handle.
5.5.2 M inimum spanning trees  Definition 24: A minimum spanning tree in a connected weighted graph is a spanning tree that has the smallest possible.
Efficient Computing k-Coverage Paths in Multihop Wireless Sensor Networks XuFei Mao, ShaoJie Tang, and Xiang-Yang Li Dept. of Computer Science, Illinois.
Two Connected Dominating Set Algorithms for Wireless Sensor Networks Overview Najla Al-Nabhan* ♦ Bowu Zhang** ♦ Mznah Al-Rodhaan* ♦ Abdullah Al-Dhelaan*
LIMITATIONS OF ALGORITHM POWER
CSCE 411H Design and Analysis of Algorithms Set 10: Lower Bounds Prof. Evdokia Nikolova* Spring 2013 CSCE 411H, Spring 2013: Set 10 1 * Slides adapted.
The full Steiner tree problem Theoretical Computer Science 306 (2003) C. L. Lu, C. Y. Tang, R. C. T. Lee Reporter: Cheng-Chung Li 2004/06/28.
1 CSC 421: Algorithm Design & Analysis Spring 2014 Complexity & lower bounds  brute force  decision trees  adversary arguments  problem reduction.
5.6 Prefix codes and optimal tree Definition 31: Codes with this property which the bit string for a letter never occurs as the first part of the bit string.
1 Chapter 8-1: Lower Bound of Comparison Sorts. 2 About this lecture Lower bound of any comparison sorting algorithm – applies to insertion sort, selection.
Computing smallest and largest repetition factorization in O(n log n) time Hiroe Inoue, Yoshiaki Matsuoka, Yuto Nakashima, Shunsuke Inenaga, Hideo Bannai,
Decision Trees DEFINITION: DECISION TREE A decision tree is a tree in which the internal nodes represent actions, the arcs represent outcomes of an action,
David Kauchak cs062 Spring 2010
Chapter 6 Transform and Conquer.
Lower Bound Theory.
Analysis and design of algorithm
Multi-Way Search Trees
Comparative RNA Structural Analysis
CS200: Algorithm Analysis
Chapter 10 Inferences on Two Samples
CS223 Advanced Data Structures and Algorithms
Speaker: Chuang-Chieh Lin National Chung Cheng University
Chapter 11 Limitations of Algorithm Power
CS 581 Tandy Warnow.
David Kauchak cs302 Spring 2012
Lecture 28 Approximation of Set Cover
Divide-and-Conquer 7 2  9 4   2   4   7
Presentation transcript:

Efficient Merging and Construction of Evolutionary Trees Andrzej Lingas,Hans Olsson, and Anna Ostlin Journal of Algorithms 2001 Reporter: Jian-Fu Dong (Dong Jian-Fu)

Abstract In this paper we study the algorithmic problem of constructing rooted evolutionary trees in the so-called experiment model. This model was first presented by Kannan, Lawler, and Warnow(J. Algorithms 21(1996) ). We present a new technique of efficiently merging partial evolutionary trees in this model. We show that two partial evolutionary trees for disjoint set of species can be merged using experiments in time O(dn), where n is the total number of species in the resulting evolutionary tree and d is its maximum degree. We prove our upper time bound on merging evolutionary tees to be asymptotically optimal. By applying our algorithm for merging evolutionary trees we obtain an O(dn log n) time bound on the problem of constructing an evolutionary tree for n species and maximum degree d from experiments. The classic O(n log n) time bound on sorting in the comparison-based model can be seen as a very special case of this upper bound

Evolutionary Tree An evolutionary tree is a tree where the leaves represent species and internal nodes represent their common ancestors.

Some definition Given a subset S of leaves of T, the partial eolutionary tree induced by S, denoted by T || S, is defined as the tree obtained by taking the minimum subtree of T connecting the species in S, and then contracting any degree 1 nodes in this subtree. For a partial evolutionary tree U, the set of its leaves will be denoted by S

Problem definition The problem of merging two partial eolutionary trees L and R, where S L ∩S R =ψ, consists of constructing the partial evolutionary tree T || (S L ∪ S R ), denoted by L ∪ R, using L, R, and access to an experiment oracle for triples (S L ∪ S R ) 3

Theorem

Theorm/Proof(2)

Theorem/proof(3)

Lower bound on merging trees

Lower bound on merging trees(2)

Conclusion As abstract, and it is an intriguing open problem whether one could establish a lower bound on the number of experiments for the evolutionary tree construction problem that would be superlinear in nd for d =O( n / log n)