Beyond Galled Trees Decomposition and Computation of Galled Networks

Size: px
Start display at page:

Download "Beyond Galled Trees Decomposition and Computation of Galled Networks"

Transcription

1 Beyond Galled Trees Decomposition and Computation of Galled Networks Daniel H. Huson & Tobias H.Kloepper RECOMB

2 Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license can be found at

3 Two Main Types of Phylogenetic Networks Implicit networks: visualization of incompatible signals Explicit networks: explicitly describe a evolutionary scenario involving reticulate events 2

4 Implicit Networks Visualization of incompatible signals Eg split network from binary characters: Haplotype data Split network Data: Cassens et al., 2003, Dusky dolphins 3

5 Explicit Networks Explicitly describe a evolutionary scenario involving reticulate events such as hybridization, HGT or recombination A B C D E F G H r 1 r 2 r 3 root 4

6 A Simple Model of Reticulate Evolution A B H C D P Hybridization HGT Recombination: Uneven Mixture mixture Order of matters of genomes reticulate events Q speciation events By C.R. Linder Ancestral genome By C.R. Linder mutations 5

7 Data For Reticulate Networks Hybridization or HGT: Different genes have different histories Input: Two or more gene trees T 1,T 2, Output: Network N that explains T 1,T 2, A B C D E A B C D E A B C D E N T 1 T 2 6

8 Data For Reticulate Networks Recombination: Recombination of closely related sequences Input: Alignment M of binary sequences Output: Network N that explains M Alignment M A: B: R: C: D: O: Additional annotation Network N 2 1, R: B: C: A: D: , O:

9 Combinatorial Approach Can be formulated in terms of splits: Every edge e of a tree T defines a split of the taxon set X: F A H e A,C,D,F,G vs B,E,H D E B G C Split encoding Σ(T) 8

10 Splits From Sequences Every non-constant binary character induces a split of the taxon set X: Alignment M A: B: C: D: E: F: ACDF vs BE Multiple columns may map to the same split Define Σ(M): set of all splits induced by M 9

11 Combinatorial Approach Hybridization or HGT: Input trees T 1,T 2, represented by splits :=Σ(T 1 ) Σ(T 2 ) (Information loss: which splits occur together in same input tree?) Recombination: Binary alignment M represented by splits :=Σ(M) (Information loss: order along sequence) 10

12 Reticulate Networks And Splits For a reticulate network N, how to define Σ(N)? Extract tree by deleting one reticulate edge for each reticulate node For each tree edge e: Obtain split from tree: A B C D E F G H r 1 r 2 r 3 e A,B,C,D,E,H vs F,G root Σ(N): set of all splits thus obtained 11

13 Parsimonious Reticulate Network Problem Input: Set of splits on a taxon set X. Output: A reticulate network N with: 1. Σ(N) 2. N contains a minimum number of reticulate nodes Such an N always exists (Baroni & Steel, 2005) To find one is NP-hard in general (Wang et al, 2001, Borderwich & Semple, 2006) Special case: N is a galled tree (Gusfield et al, ) 12

14 The Galled Tree Property Dan Gusfield et al ( ): If a solution exists that has the galled tree property, then it can be computed efficiently 13

15 The Galled Tree Property A reticulation is a gall, if it is cycle disjoint to all others P R Q A B C D E F Reticulation at P is a gall, at Q is a gall Addition of R destroys gall property for Q Gall property is fragile 14

16 The Loose Gall Property A reticulation is a loose gall, if it has a cycle whose backbone consists only of tree edges P R Q A B C D E F P, Q and R are loose galls Not fragile: Adding taxa doesn t destroy property 15

17 The Galled Network Property New definition: A reticulate network is a galled network, if all reticulations are loose galls. How to compute them? The Decomposition Theorem 16

18 Input: Computing A Galled Network Set of splits on X={A,B,,I} that comes from a network, either via trees or binary sequences, e.g.: G H I A B C D E F 17

19 Computing A Galled Network Assume we know G,H,I are reticulate taxa Where to attach G, H, I? H I G A B C D E F Induced splits Extended splits X-{G,H,I} X-{H,I} Orient edges to show where splits place G Attach G to ends of target path 18

20 Computing A Galled Network Assume we know G,H,I are reticulate taxa Where to attach G, H, I? G I H A B C D E F Induced splits Extended splits X-{G,H,I} X-{G,I} Orient edges to show where splits place H Attach H to ends of target path 19

21 Computing A Galled Network Assume we know G,H,I are reticulate taxa Where to attach G, H, I? G H I A B C D E F I Induced splits Extended splits X-{G,H,I} X-{G,H} Orient edges to show where splits place I Attach I to ends of target path 20

22 Computing A Galled Network Assume we know G,H,I are reticulate taxa Where to attach G, H, I? G H A B C D E F I If Σ(N), then return N 21

23 Algorithm Input: Set of splits on X, parameter k In increasing order of size k: Consider a set of taxa R X If X-R is compatible: Attempt to attach each r R to T( X-R ) If successful, construct network N If Σ(N), return N Return fail FPT, for fixed maximum size k of R 22

24 Decomposition Conjecture (Dan Gusfield) Input trees Split network Minimal reticulate network 23

25 Decomposition Conjecture Each incompatibility component can be considered independently: 1. component 2. component (Gusfield et al. 2005) (Huson et al. 2005) 24

26 The Decomposition Theorem Let of be a set of splits. If there exists a galled network N with Σ(N), then there exists a minimal network N min that has the decomposition property. To compute N min we can consider each component separately 25

27 Proof Easy, assuming non-degenerate: For every tree node v there exists a path of tree edges from v down to some leaf w. A B C D E F G H v non-degenerate root Degenerate node, no tree path to leaf 26

28 Consider any reticulation cycle A Proof a X Y R b B Any split S Σ(e) is incompatible with all S Σ(a) or S Σ(b): S contains either AXR BY or AX BYR S contains AR XYB S contains AXY BR e 27

29 Implementation Available in the latest version of SplitsTree4 Interactive program for phylogenetic analysis using trees and networks (Huson and Bryant, MBE, 2006) 28

30 Reticulate Network with 4 reticulations Data: Kumar et al, Restriction map of the rdna cistron, culicine mosquitos 29

31 Reticulate cladogram 30

32 Conclusion & Outlook Galled networks go beyond galled trees A user-friendly implementation is available in the latest version of SplitsTree4 Decomposition Conjecture unsolved in general All current methods based on combinatorics, thus are sensitive to false-positive splits More robust methods for computation of phylogenetic networks required 31

33 32

Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation

Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published

More information

Splits and Phylogenetic Networks. Daniel H. Huson

Splits and Phylogenetic Networks. Daniel H. Huson Splits and Phylogenetic Networks Daniel H. Huson aris, June 21, 2005 1 2 Contents 1. Phylogenetic trees 2. Splits networks 3. Consensus networks 4. Hybridization and reticulate networks 5. Recombination

More information

Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation

Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation Daniel H. Huson Stockholm, May 28, 2005 Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version

More information

Phylogenetic Networks, Trees, and Clusters

Phylogenetic Networks, Trees, and Clusters Phylogenetic Networks, Trees, and Clusters Luay Nakhleh 1 and Li-San Wang 2 1 Department of Computer Science Rice University Houston, TX 77005, USA nakhleh@cs.rice.edu 2 Department of Biology University

More information

A Phylogenetic Network Construction due to Constrained Recombination

A Phylogenetic Network Construction due to Constrained Recombination A Phylogenetic Network Construction due to Constrained Recombination Mohd. Abdul Hai Zahid Research Scholar Research Supervisors: Dr. R.C. Joshi Dr. Ankush Mittal Department of Electronics and Computer

More information

TheDisk-Covering MethodforTree Reconstruction

TheDisk-Covering MethodforTree Reconstruction TheDisk-Covering MethodforTree Reconstruction Daniel Huson PACM, Princeton University Bonn, 1998 1 Copyright (c) 2008 Daniel Huson. Permission is granted to copy, distribute and/or modify this document

More information

Finding a gene tree in a phylogenetic network Philippe Gambette

Finding a gene tree in a phylogenetic network Philippe Gambette LRI-LIX BioInfo Seminar 19/01/2017 - Palaiseau Finding a gene tree in a phylogenetic network Philippe Gambette Outline Phylogenetic networks Classes of phylogenetic networks The Tree Containment Problem

More information

From graph classes to phylogenetic networks Philippe Gambette

From graph classes to phylogenetic networks Philippe Gambette 40 années d'algorithmique de graphes 40 Years of Graphs and Algorithms 11/10/2018 - Paris From graph classes to phylogenetic networks Philippe Gambette Outline Discovering graph classes with Michel An

More information

THE THREE-STATE PERFECT PHYLOGENY PROBLEM REDUCES TO 2-SAT

THE THREE-STATE PERFECT PHYLOGENY PROBLEM REDUCES TO 2-SAT COMMUNICATIONS IN INFORMATION AND SYSTEMS c 2009 International Press Vol. 9, No. 4, pp. 295-302, 2009 001 THE THREE-STATE PERFECT PHYLOGENY PROBLEM REDUCES TO 2-SAT DAN GUSFIELD AND YUFENG WU Abstract.

More information

Properties of normal phylogenetic networks

Properties of normal phylogenetic networks Properties of normal phylogenetic networks Stephen J. Willson Department of Mathematics Iowa State University Ames, IA 50011 USA swillson@iastate.edu August 13, 2009 Abstract. A phylogenetic network is

More information

Tree-average distances on certain phylogenetic networks have their weights uniquely determined

Tree-average distances on certain phylogenetic networks have their weights uniquely determined Tree-average distances on certain phylogenetic networks have their weights uniquely determined Stephen J. Willson Department of Mathematics Iowa State University Ames, IA 50011 USA swillson@iastate.edu

More information

Regular networks are determined by their trees

Regular networks are determined by their trees Regular networks are determined by their trees Stephen J. Willson Department of Mathematics Iowa State University Ames, IA 50011 USA swillson@iastate.edu February 17, 2009 Abstract. A rooted acyclic digraph

More information

A new algorithm to construct phylogenetic networks from trees

A new algorithm to construct phylogenetic networks from trees A new algorithm to construct phylogenetic networks from trees J. Wang College of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia, China Corresponding author: J. Wang E-mail: wangjuanangle@hit.edu.cn

More information

Integer Programming for Phylogenetic Network Problems

Integer Programming for Phylogenetic Network Problems Integer Programming for Phylogenetic Network Problems D. Gusfield University of California, Davis Presented at the National University of Singapore, July 27, 2015.! There are many important phylogeny problems

More information

Phylogenetic Networks with Recombination

Phylogenetic Networks with Recombination Phylogenetic Networks with Recombination October 17 2012 Recombination All DNA is recombinant DNA... [The] natural process of recombination and mutation have acted throughout evolution... Genetic exchange

More information

Intraspecific gene genealogies: trees grafting into networks

Intraspecific gene genealogies: trees grafting into networks Intraspecific gene genealogies: trees grafting into networks by David Posada & Keith A. Crandall Kessy Abarenkov Tartu, 2004 Article describes: Population genetics principles Intraspecific genetic variation

More information

NOTE ON THE HYBRIDIZATION NUMBER AND SUBTREE DISTANCE IN PHYLOGENETICS

NOTE ON THE HYBRIDIZATION NUMBER AND SUBTREE DISTANCE IN PHYLOGENETICS NOTE ON THE HYBRIDIZATION NUMBER AND SUBTREE DISTANCE IN PHYLOGENETICS PETER J. HUMPHRIES AND CHARLES SEMPLE Abstract. For two rooted phylogenetic trees T and T, the rooted subtree prune and regraft distance

More information

arxiv: v1 [q-bio.pe] 1 Jun 2014

arxiv: v1 [q-bio.pe] 1 Jun 2014 THE MOST PARSIMONIOUS TREE FOR RANDOM DATA MAREIKE FISCHER, MICHELLE GALLA, LINA HERBST AND MIKE STEEL arxiv:46.27v [q-bio.pe] Jun 24 Abstract. Applying a method to reconstruct a phylogenetic tree from

More information

An introduction to phylogenetic networks

An introduction to phylogenetic networks An introduction to phylogenetic networks Steven Kelk Department of Knowledge Engineering (DKE) Maastricht University Email: steven.kelk@maastrichtuniversity.nl Web: http://skelk.sdf-eu.org Genome sequence,

More information

Phylogenetic networks: overview, subclasses and counting problems Philippe Gambette

Phylogenetic networks: overview, subclasses and counting problems Philippe Gambette ANR-FWF-MOST meeting 2018-10-30 - Wien Phylogenetic networks: overview, subclasses and counting problems Philippe Gambette Outline An introduction to phylogenetic networks Classes of phylogenetic networks

More information

ALGORITHMIC STRATEGIES FOR ESTIMATING THE AMOUNT OF RETICULATION FROM A COLLECTION OF GENE TREES

ALGORITHMIC STRATEGIES FOR ESTIMATING THE AMOUNT OF RETICULATION FROM A COLLECTION OF GENE TREES ALGORITHMIC STRATEGIES FOR ESTIMATING THE AMOUNT OF RETICULATION FROM A COLLECTION OF GENE TREES H. J. Park and G. Jin and L. Nakhleh Department of Computer Science, Rice University, 6 Main Street, Houston,

More information

ISMB-Tutorial: Introduction to Phylogenetic Networks. Daniel H. Huson

ISMB-Tutorial: Introduction to Phylogenetic Networks. Daniel H. Huson ISMB-Tutorial: Introduction to Phylogenetic Networks Daniel H. Huson Center for Bioinformatics, Tübingen University Sand 14, 72075 Tübingen, Germany www-ab.informatik.uni-tuebingen.de June 25, 2005 Contents

More information

Efficient Parsimony-based Methods for Phylogenetic Network Reconstruction

Efficient Parsimony-based Methods for Phylogenetic Network Reconstruction BIOINFORMATICS Vol. 00 no. 00 2006 Pages 1 7 Efficient Parsimony-based Methods for Phylogenetic Network Reconstruction Guohua Jin a, Luay Nakhleh a, Sagi Snir b, Tamir Tuller c a Dept. of Computer Science,

More information

Introduction to Phylogenetic Networks

Introduction to Phylogenetic Networks Introduction to Phylogenetic Networks Daniel H. Huson GCB 2006, Tübingen,, September 19, 2006 1 Contents 1. Phylogenetic trees 2. Consensus networks and super networks 3. Hybridization and reticulate networks

More information

Evolutionary Tree Analysis. Overview

Evolutionary Tree Analysis. Overview CSI/BINF 5330 Evolutionary Tree Analysis Young-Rae Cho Associate Professor Department of Computer Science Baylor University Overview Backgrounds Distance-Based Evolutionary Tree Reconstruction Character-Based

More information

UNICYCLIC NETWORKS: COMPATIBILITY AND ENUMERATION

UNICYCLIC NETWORKS: COMPATIBILITY AND ENUMERATION UNICYCLIC NETWORKS: COMPATIBILITY AND ENUMERATION CHARLES SEMPLE AND MIKE STEEL Abstract. Graphs obtained from a binary leaf labelled ( phylogenetic ) tree by adding an edge so as to introduce a cycle

More information

Improved maximum parsimony models for phylogenetic networks

Improved maximum parsimony models for phylogenetic networks Improved maximum parsimony models for phylogenetic networks Leo van Iersel Mark Jones Celine Scornavacca December 20, 207 Abstract Phylogenetic networks are well suited to represent evolutionary histories

More information

Solving the Tree Containment Problem for Genetically Stable Networks in Quadratic Time

Solving the Tree Containment Problem for Genetically Stable Networks in Quadratic Time Solving the Tree Containment Problem for Genetically Stable Networks in Quadratic Time Philippe Gambette, Andreas D.M. Gunawan, Anthony Labarre, Stéphane Vialette, Louxin Zhang To cite this version: Philippe

More information

Reconstruction of certain phylogenetic networks from their tree-average distances

Reconstruction of certain phylogenetic networks from their tree-average distances Reconstruction of certain phylogenetic networks from their tree-average distances Stephen J. Willson Department of Mathematics Iowa State University Ames, IA 50011 USA swillson@iastate.edu October 10,

More information

Page 1. Evolutionary Trees. Why build evolutionary tree? Outline

Page 1. Evolutionary Trees. Why build evolutionary tree? Outline Page Evolutionary Trees Russ. ltman MI S 7 Outline. Why build evolutionary trees?. istance-based vs. character-based methods. istance-based: Ultrametric Trees dditive Trees. haracter-based: Perfect phylogeny

More information

Integer Programming in Computational Biology. D. Gusfield University of California, Davis Presented December 12, 2016.!

Integer Programming in Computational Biology. D. Gusfield University of California, Davis Presented December 12, 2016.! Integer Programming in Computational Biology D. Gusfield University of California, Davis Presented December 12, 2016. There are many important phylogeny problems that depart from simple tree models: Missing

More information

Phylogenetics: Parsimony

Phylogenetics: Parsimony 1 Phylogenetics: Parsimony COMP 571 Luay Nakhleh, Rice University he Problem 2 Input: Multiple alignment of a set S of sequences Output: ree leaf-labeled with S Assumptions Characters are mutually independent

More information

A 3-APPROXIMATION ALGORITHM FOR THE SUBTREE DISTANCE BETWEEN PHYLOGENIES. 1. Introduction

A 3-APPROXIMATION ALGORITHM FOR THE SUBTREE DISTANCE BETWEEN PHYLOGENIES. 1. Introduction A 3-APPROXIMATION ALGORITHM FOR THE SUBTREE DISTANCE BETWEEN PHYLOGENIES MAGNUS BORDEWICH 1, CATHERINE MCCARTIN 2, AND CHARLES SEMPLE 3 Abstract. In this paper, we give a (polynomial-time) 3-approximation

More information

Dr. Amira A. AL-Hosary

Dr. Amira A. AL-Hosary Phylogenetic analysis Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut University-Egypt Phylogenetic Basics: Biological

More information

Restricted trees: simplifying networks with bottlenecks

Restricted trees: simplifying networks with bottlenecks Restricted trees: simplifying networks with bottlenecks Stephen J. Willson Department of Mathematics Iowa State University Ames, IA 50011 USA swillson@iastate.edu February 17, 2011 Abstract. Suppose N

More information

A CLUSTER REDUCTION FOR COMPUTING THE SUBTREE DISTANCE BETWEEN PHYLOGENIES

A CLUSTER REDUCTION FOR COMPUTING THE SUBTREE DISTANCE BETWEEN PHYLOGENIES A CLUSTER REDUCTION FOR COMPUTING THE SUBTREE DISTANCE BETWEEN PHYLOGENIES SIMONE LINZ AND CHARLES SEMPLE Abstract. Calculating the rooted subtree prune and regraft (rspr) distance between two rooted binary

More information

1.1 The (rooted, binary-character) Perfect-Phylogeny Problem

1.1 The (rooted, binary-character) Perfect-Phylogeny Problem Contents 1 Trees First 3 1.1 Rooted Perfect-Phylogeny...................... 3 1.1.1 Alternative Definitions.................... 5 1.1.2 The Perfect-Phylogeny Problem and Solution....... 7 1.2 Alternate,

More information

What is Phylogenetics

What is Phylogenetics What is Phylogenetics Phylogenetics is the area of research concerned with finding the genetic connections and relationships between species. The basic idea is to compare specific characters (features)

More information

Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut

Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut University-Egypt Phylogenetic analysis Phylogenetic Basics: Biological

More information

Charles Semple, Philip Daniel, Wim Hordijk, Roderic D M Page, and Mike Steel

Charles Semple, Philip Daniel, Wim Hordijk, Roderic D M Page, and Mike Steel SUPERTREE ALGORITHMS FOR ANCESTRAL DIVERGENCE DATES AND NESTED TAXA Charles Semple, Philip Daniel, Wim Hordijk, Roderic D M Page, and Mike Steel Department of Mathematics and Statistics University of Canterbury

More information

Bioinformatics Advance Access published August 23, 2006

Bioinformatics Advance Access published August 23, 2006 Bioinformatics Advance Access published August 23, 2006 BIOINFORMATICS Maximum Likelihood of Phylogenetic Networks Guohua Jin a Luay Nakhleh a Sagi Snir b Tamir Tuller c a Dept. of Computer Science Rice

More information

Consistency Index (CI)

Consistency Index (CI) Consistency Index (CI) minimum number of changes divided by the number required on the tree. CI=1 if there is no homoplasy negatively correlated with the number of species sampled Retention Index (RI)

More information

NJMerge: A generic technique for scaling phylogeny estimation methods and its application to species trees

NJMerge: A generic technique for scaling phylogeny estimation methods and its application to species trees NJMerge: A generic technique for scaling phylogeny estimation methods and its application to species trees Erin Molloy and Tandy Warnow {emolloy2, warnow}@illinois.edu University of Illinois at Urbana

More information

Phylogeny and systematics. Why are these disciplines important in evolutionary biology and how are they related to each other?

Phylogeny and systematics. Why are these disciplines important in evolutionary biology and how are they related to each other? Phylogeny and systematics Why are these disciplines important in evolutionary biology and how are they related to each other? Phylogeny and systematics Phylogeny: the evolutionary history of a species

More information

Aphylogenetic network is a generalization of a phylogenetic tree, allowing properties that are not tree-like.

Aphylogenetic network is a generalization of a phylogenetic tree, allowing properties that are not tree-like. INFORMS Journal on Computing Vol. 16, No. 4, Fall 2004, pp. 459 469 issn 0899-1499 eissn 1526-5528 04 1604 0459 informs doi 10.1287/ijoc.1040.0099 2004 INFORMS The Fine Structure of Galls in Phylogenetic

More information

Phylogenetic analyses. Kirsi Kostamo

Phylogenetic analyses. Kirsi Kostamo Phylogenetic analyses Kirsi Kostamo The aim: To construct a visual representation (a tree) to describe the assumed evolution occurring between and among different groups (individuals, populations, species,

More information

Distances that Perfectly Mislead

Distances that Perfectly Mislead Syst. Biol. 53(2):327 332, 2004 Copyright c Society of Systematic Biologists ISSN: 1063-5157 print / 1076-836X online DOI: 10.1080/10635150490423809 Distances that Perfectly Mislead DANIEL H. HUSON 1 AND

More information

CHAPTERS 24-25: Evidence for Evolution and Phylogeny

CHAPTERS 24-25: Evidence for Evolution and Phylogeny CHAPTERS 24-25: Evidence for Evolution and Phylogeny 1. For each of the following, indicate how it is used as evidence of evolution by natural selection or shown as an evolutionary trend: a. Paleontology

More information

Fast Phylogenetic Methods for the Analysis of Genome Rearrangement Data: An Empirical Study

Fast Phylogenetic Methods for the Analysis of Genome Rearrangement Data: An Empirical Study Fast Phylogenetic Methods for the Analysis of Genome Rearrangement Data: An Empirical Study Li-San Wang Robert K. Jansen Dept. of Computer Sciences Section of Integrative Biology University of Texas, Austin,

More information

Supertree Algorithms for Ancestral Divergence Dates and Nested Taxa

Supertree Algorithms for Ancestral Divergence Dates and Nested Taxa Supertree Algorithms for Ancestral Divergence Dates and Nested Taxa Charles Semple 1, Philip Daniel 1, Wim Hordijk 1, Roderic D. M. Page 2, and Mike Steel 1 1 Biomathematics Research Centre, Department

More information

Higher Order ODE's (3A) Young Won Lim 12/27/15

Higher Order ODE's (3A) Young Won Lim 12/27/15 Higher Order ODE's (3A) Copyright (c) 2011-2015 Young W. Lim. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or

More information

Inferring a level-1 phylogenetic network from a dense set of rooted triplets

Inferring a level-1 phylogenetic network from a dense set of rooted triplets Theoretical Computer Science 363 (2006) 60 68 www.elsevier.com/locate/tcs Inferring a level-1 phylogenetic network from a dense set of rooted triplets Jesper Jansson a,, Wing-Kin Sung a,b, a School of

More information

Algorithms in Bioinformatics

Algorithms in Bioinformatics Algorithms in Bioinformatics Sami Khuri Department of Computer Science San José State University San José, California, USA khuri@cs.sjsu.edu www.cs.sjsu.edu/faculty/khuri Distance Methods Character Methods

More information

Algorithms for phylogeny construction

Algorithms for phylogeny construction Algorithms for phylogeny construction A Hybrid Micro-Macroevolutionary Approach to Gene Tree Reconstruction ICE-TCS Inaugural Symposium Bjarni V. Halldórsson April 30, 2005 1 Character based phylogeny

More information

Chapter 26: Phylogeny and the Tree of Life Phylogenies Show Evolutionary Relationships

Chapter 26: Phylogeny and the Tree of Life Phylogenies Show Evolutionary Relationships Chapter 26: Phylogeny and the Tree of Life You Must Know The taxonomic categories and how they indicate relatedness. How systematics is used to develop phylogenetic trees. How to construct a phylogenetic

More information

Relations (3A) Young Won Lim 3/27/18

Relations (3A) Young Won Lim 3/27/18 Relations (3A) Copyright (c) 2015 2018 Young W. Lim. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later

More information

An Overview of Combinatorial Methods for Haplotype Inference

An Overview of Combinatorial Methods for Haplotype Inference An Overview of Combinatorial Methods for Haplotype Inference Dan Gusfield 1 Department of Computer Science, University of California, Davis Davis, CA. 95616 Abstract A current high-priority phase of human

More information

AP Biology. Cladistics

AP Biology. Cladistics Cladistics Kingdom Summary Review slide Review slide Classification Old 5 Kingdom system Eukaryote Monera, Protists, Plants, Fungi, Animals New 3 Domain system reflects a greater understanding of evolution

More information

Zhongyi Xiao. Correlation. In probability theory and statistics, correlation indicates the

Zhongyi Xiao. Correlation. In probability theory and statistics, correlation indicates the Character Correlation Zhongyi Xiao Correlation In probability theory and statistics, correlation indicates the strength and direction of a linear relationship between two random variables. In general statistical

More information

RECOVERING NORMAL NETWORKS FROM SHORTEST INTER-TAXA DISTANCE INFORMATION

RECOVERING NORMAL NETWORKS FROM SHORTEST INTER-TAXA DISTANCE INFORMATION RECOVERING NORMAL NETWORKS FROM SHORTEST INTER-TAXA DISTANCE INFORMATION MAGNUS BORDEWICH, KATHARINA T. HUBER, VINCENT MOULTON, AND CHARLES SEMPLE Abstract. Phylogenetic networks are a type of leaf-labelled,

More information

I. Short Answer Questions DO ALL QUESTIONS

I. Short Answer Questions DO ALL QUESTIONS EVOLUTION 313 FINAL EXAM Part 1 Saturday, 7 May 2005 page 1 I. Short Answer Questions DO ALL QUESTIONS SAQ #1. Please state and BRIEFLY explain the major objectives of this course in evolution. Recall

More information

Estimating Recombination Rates. LRH selection test, and recombination

Estimating Recombination Rates. LRH selection test, and recombination Estimating Recombination Rates LRH selection test, and recombination Recall that LRH tests for selection by looking at frequencies of specific haplotypes. Clearly the test is dependent on the recombination

More information

Phylogenetic Tree Reconstruction

Phylogenetic Tree Reconstruction I519 Introduction to Bioinformatics, 2011 Phylogenetic Tree Reconstruction Yuzhen Ye (yye@indiana.edu) School of Informatics & Computing, IUB Evolution theory Speciation Evolution of new organisms is driven

More information

STEM-hy: Species Tree Estimation using Maximum likelihood (with hybridization)

STEM-hy: Species Tree Estimation using Maximum likelihood (with hybridization) STEM-hy: Species Tree Estimation using Maximum likelihood (with hybridization) Laura Salter Kubatko Departments of Statistics and Evolution, Ecology, and Organismal Biology The Ohio State University kubatko.2@osu.edu

More information

Microbial Taxonomy and the Evolution of Diversity

Microbial Taxonomy and the Evolution of Diversity 19 Microbial Taxonomy and the Evolution of Diversity Copyright McGraw-Hill Global Education Holdings, LLC. Permission required for reproduction or display. 1 Taxonomy Introduction to Microbial Taxonomy

More information

Solving the Maximum Agreement Subtree and Maximum Comp. Tree problems on bounded degree trees. Sylvain Guillemot, François Nicolas.

Solving the Maximum Agreement Subtree and Maximum Comp. Tree problems on bounded degree trees. Sylvain Guillemot, François Nicolas. Solving the Maximum Agreement Subtree and Maximum Compatible Tree problems on bounded degree trees LIRMM, Montpellier France 4th July 2006 Introduction The Mast and Mct problems: given a set of evolutionary

More information

A PARSIMONY APPROACH TO ANALYSIS OF HUMAN SEGMENTAL DUPLICATIONS

A PARSIMONY APPROACH TO ANALYSIS OF HUMAN SEGMENTAL DUPLICATIONS A PARSIMONY APPROACH TO ANALYSIS OF HUMAN SEGMENTAL DUPLICATIONS CRYSTAL L. KAHN and BENJAMIN J. RAPHAEL Box 1910, Brown University Department of Computer Science & Center for Computational Molecular Biology

More information

Let S be a set of n species. A phylogeny is a rooted tree with n leaves, each of which is uniquely

Let S be a set of n species. A phylogeny is a rooted tree with n leaves, each of which is uniquely JOURNAL OF COMPUTATIONAL BIOLOGY Volume 8, Number 1, 2001 Mary Ann Liebert, Inc. Pp. 69 78 Perfect Phylogenetic Networks with Recombination LUSHENG WANG, 1 KAIZHONG ZHANG, 2 and LOUXIN ZHANG 3 ABSTRACT

More information

Algebraic Statistics Tutorial I

Algebraic Statistics Tutorial I Algebraic Statistics Tutorial I Seth Sullivant North Carolina State University June 9, 2012 Seth Sullivant (NCSU) Algebraic Statistics June 9, 2012 1 / 34 Introduction to Algebraic Geometry Let R[p] =

More information

Elements of Bioinformatics 14F01 TP5 -Phylogenetic analysis

Elements of Bioinformatics 14F01 TP5 -Phylogenetic analysis Elements of Bioinformatics 14F01 TP5 -Phylogenetic analysis 10 December 2012 - Corrections - Exercise 1 Non-vertebrate chordates generally possess 2 homologs, vertebrates 3 or more gene copies; a Drosophila

More information

Haplotyping as Perfect Phylogeny: A direct approach

Haplotyping as Perfect Phylogeny: A direct approach Haplotyping as Perfect Phylogeny: A direct approach Vineet Bafna Dan Gusfield Giuseppe Lancia Shibu Yooseph February 7, 2003 Abstract A full Haplotype Map of the human genome will prove extremely valuable

More information

arxiv: v3 [q-bio.pe] 1 May 2014

arxiv: v3 [q-bio.pe] 1 May 2014 ON COMPUTING THE MAXIMUM PARSIMONY SCORE OF A PHYLOGENETIC NETWORK MAREIKE FISCHER, LEO VAN IERSEL, STEVEN KELK, AND CELINE SCORNAVACCA arxiv:32.243v3 [q-bio.pe] May 24 Abstract. Phylogenetic networks

More information

UoN, CAS, DBSC BIOL102 lecture notes by: Dr. Mustafa A. Mansi. The Phylogenetic Systematics (Phylogeny and Systematics)

UoN, CAS, DBSC BIOL102 lecture notes by: Dr. Mustafa A. Mansi. The Phylogenetic Systematics (Phylogeny and Systematics) - Phylogeny? - Systematics? The Phylogenetic Systematics (Phylogeny and Systematics) - Phylogenetic systematics? Connection between phylogeny and classification. - Phylogenetic systematics informs the

More information

Higher Order ODE's (3A) Young Won Lim 7/7/14

Higher Order ODE's (3A) Young Won Lim 7/7/14 Higher Order ODE's (3A) Copyright (c) 2011-2014 Young W. Lim. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or

More information

Perfect Phylogenetic Networks with Recombination Λ

Perfect Phylogenetic Networks with Recombination Λ Perfect Phylogenetic Networks with Recombination Λ Lusheng Wang Dept. of Computer Sci. City Univ. of Hong Kong 83 Tat Chee Avenue Hong Kong lwang@cs.cityu.edu.hk Kaizhong Zhang Dept. of Computer Sci. Univ.

More information

Matrix Transformation (2A) Young Won Lim 11/10/12

Matrix Transformation (2A) Young Won Lim 11/10/12 Matrix (A Copyright (c 0 Young W. im. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation icense, Version. or any later version published

More information

Theory of Evolution Charles Darwin

Theory of Evolution Charles Darwin Theory of Evolution Charles arwin 858-59: Origin of Species 5 year voyage of H.M.S. eagle (83-36) Populations have variations. Natural Selection & Survival of the fittest: nature selects best adapted varieties

More information

Phylogenetic inference

Phylogenetic inference Phylogenetic inference Bas E. Dutilh Systems Biology: Bioinformatic Data Analysis Utrecht University, March 7 th 016 After this lecture, you can discuss (dis-) advantages of different information types

More information

RECOVERING A PHYLOGENETIC TREE USING PAIRWISE CLOSURE OPERATIONS

RECOVERING A PHYLOGENETIC TREE USING PAIRWISE CLOSURE OPERATIONS RECOVERING A PHYLOGENETIC TREE USING PAIRWISE CLOSURE OPERATIONS KT Huber, V Moulton, C Semple, and M Steel Department of Mathematics and Statistics University of Canterbury Private Bag 4800 Christchurch,

More information

General CORDIC Description (1A)

General CORDIC Description (1A) General CORDIC Description (1A) Copyright (c) 2010, 2011, 2012 Young W. Lim. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License,

More information

Phylogeny. Properties of Trees. Properties of Trees. Trees represent the order of branching only. Phylogeny: Taxon: a unit of classification

Phylogeny. Properties of Trees. Properties of Trees. Trees represent the order of branching only. Phylogeny: Taxon: a unit of classification Multiple sequence alignment global local Evolutionary tree reconstruction Pairwise sequence alignment (global and local) Substitution matrices Gene Finding Protein structure prediction N structure prediction

More information

arxiv: v5 [q-bio.pe] 24 Oct 2016

arxiv: v5 [q-bio.pe] 24 Oct 2016 On the Quirks of Maximum Parsimony and Likelihood on Phylogenetic Networks Christopher Bryant a, Mareike Fischer b, Simone Linz c, Charles Semple d arxiv:1505.06898v5 [q-bio.pe] 24 Oct 2016 a Statistics

More information

The Multi-State Perfect Phylogeny Problem with Missing and Removable Data: Solutions via Integer-Programming and Chordal Graph Theory

The Multi-State Perfect Phylogeny Problem with Missing and Removable Data: Solutions via Integer-Programming and Chordal Graph Theory The Multi-State Perfect Phylogeny Problem with Missing and Removable Data: Solutions via Integer-Programming and Chordal Graph Theory Dan Gusfield Department of Computer Science, University of California,

More information

Theory of Evolution. Charles Darwin

Theory of Evolution. Charles Darwin Theory of Evolution harles arwin 858-59: Origin of Species 5 year voyage of H.M.S. eagle (8-6) Populations have variations. Natural Selection & Survival of the fittest: nature selects best adapted varieties

More information

POPULATION GENETICS Winter 2005 Lecture 17 Molecular phylogenetics

POPULATION GENETICS Winter 2005 Lecture 17 Molecular phylogenetics POPULATION GENETICS Winter 2005 Lecture 17 Molecular phylogenetics - in deriving a phylogeny our goal is simply to reconstruct the historical relationships between a group of taxa. - before we review the

More information

Phylogenetics. BIOL 7711 Computational Bioscience

Phylogenetics. BIOL 7711 Computational Bioscience Consortium for Comparative Genomics! University of Colorado School of Medicine Phylogenetics BIOL 7711 Computational Bioscience Biochemistry and Molecular Genetics Computational Bioscience Program Consortium

More information

Exploring Treespace. Katherine St. John. Lehman College & the Graduate Center. City University of New York. 20 June 2011

Exploring Treespace. Katherine St. John. Lehman College & the Graduate Center. City University of New York. 20 June 2011 Exploring Treespace Katherine St. John Lehman College & the Graduate Center City University of New York 20 June 2011 (Joint work with the Treespace Working Group, CUNY: Ann Marie Alcocer, Kadian Brown,

More information

CS 394C Algorithms for Computational Biology. Tandy Warnow Spring 2012

CS 394C Algorithms for Computational Biology. Tandy Warnow Spring 2012 CS 394C Algorithms for Computational Biology Tandy Warnow Spring 2012 Biology: 21st Century Science! When the human genome was sequenced seven years ago, scientists knew that most of the major scientific

More information

On the Subnet Prune and Regraft distance

On the Subnet Prune and Regraft distance On the Subnet Prune and Regraft distance Jonathan Klawitter and Simone Linz Department of Computer Science, University of Auckland, New Zealand jo. klawitter@ gmail. com, s. linz@ auckland. ac. nz arxiv:805.07839v

More information

Homework Assignment, Evolutionary Systems Biology, Spring Homework Part I: Phylogenetics:

Homework Assignment, Evolutionary Systems Biology, Spring Homework Part I: Phylogenetics: Homework Assignment, Evolutionary Systems Biology, Spring 2009. Homework Part I: Phylogenetics: Introduction. The objective of this assignment is to understand the basics of phylogenetic relationships

More information

Biology 211 (2) Week 1 KEY!

Biology 211 (2) Week 1 KEY! Biology 211 (2) Week 1 KEY Chapter 1 KEY FIGURES: 1.2, 1.3, 1.4, 1.5, 1.6, 1.7 VOCABULARY: Adaptation: a trait that increases the fitness Cells: a developed, system bound with a thin outer layer made of

More information

9/30/11. Evolution theory. Phylogenetic Tree Reconstruction. Phylogenetic trees (binary trees) Phylogeny (phylogenetic tree)

9/30/11. Evolution theory. Phylogenetic Tree Reconstruction. Phylogenetic trees (binary trees) Phylogeny (phylogenetic tree) I9 Introduction to Bioinformatics, 0 Phylogenetic ree Reconstruction Yuzhen Ye (yye@indiana.edu) School of Informatics & omputing, IUB Evolution theory Speciation Evolution of new organisms is driven by

More information

Introduction to characters and parsimony analysis

Introduction to characters and parsimony analysis Introduction to characters and parsimony analysis Genetic Relationships Genetic relationships exist between individuals within populations These include ancestordescendent relationships and more indirect

More information

Notes 3 : Maximum Parsimony

Notes 3 : Maximum Parsimony Notes 3 : Maximum Parsimony MATH 833 - Fall 2012 Lecturer: Sebastien Roch References: [SS03, Chapter 5], [DPV06, Chapter 8] 1 Beyond Perfect Phylogenies Viewing (full, i.e., defined on all of X) binary

More information

A program to compute the soft Robinson Foulds distance between phylogenetic networks

A program to compute the soft Robinson Foulds distance between phylogenetic networks The Author(s) BMC Genomics 217, 18(Suppl 2):111 DOI 1.1186/s12864-17-35-5 RESEARCH Open Access A program to compute the soft Robinson Foulds distance between phylogenetic networks Bingxin Lu 1, Louxin

More information

Dispersion (3A) 1-D Dispersion. Young W. Lim 10/15/13

Dispersion (3A) 1-D Dispersion. Young W. Lim 10/15/13 1-D Dispersion Copyright (c) 013. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1. or any later version published

More information

Chapter 26 Phylogeny and the Tree of Life

Chapter 26 Phylogeny and the Tree of Life Chapter 26 Phylogeny and the Tree of Life Chapter focus Shifting from the process of how evolution works to the pattern evolution produces over time. Phylogeny Phylon = tribe, geny = genesis or origin

More information

Integrative Biology 200 "PRINCIPLES OF PHYLOGENETICS" Spring 2016 University of California, Berkeley. Parsimony & Likelihood [draft]

Integrative Biology 200 PRINCIPLES OF PHYLOGENETICS Spring 2016 University of California, Berkeley. Parsimony & Likelihood [draft] Integrative Biology 200 "PRINCIPLES OF PHYLOGENETICS" Spring 2016 University of California, Berkeley K.W. Will Parsimony & Likelihood [draft] 1. Hennig and Parsimony: Hennig was not concerned with parsimony

More information

Supplementary Materials for

Supplementary Materials for advances.sciencemag.org/cgi/content/full/1/8/e1500527/dc1 Supplementary Materials for A phylogenomic data-driven exploration of viral origins and evolution The PDF file includes: Arshan Nasir and Gustavo

More information

Using Ensembles of Hidden Markov Models for Grand Challenges in Bioinformatics

Using Ensembles of Hidden Markov Models for Grand Challenges in Bioinformatics Using Ensembles of Hidden Markov Models for Grand Challenges in Bioinformatics Tandy Warnow Founder Professor of Engineering The University of Illinois at Urbana-Champaign http://tandy.cs.illinois.edu

More information