This volume presents a compelling collection of state-of-the-art work in algorithmic computational biology, honoring the legacy of Professor Bernard M.E. Moret in this field. Reflecting the wide-ranging influences of Prof. Moret's research, the coverage encompasses such areas as phylogenetic tree and network estimation, genome rearrangements, cancer phylogeny, species trees, divide-and-conquer strategies, and integer linear programming. Each self-contained chapter provides an introduction to a cutting-edge problem of particular computational and mathematical interest.Topics and features: addresses the challenges in developing accurate and efficient software for the NP-hard maximum likelihood phylogeny estimation problem; describes the inference of species trees, covering strategies to scale phylogeny estimation methods to large datasets, and the construction of taxonomic supertrees; discusses the inference of ultrametric distances from additive distance matrices, and the inference of ancestral genomes under genome rearrangement events; reviews different techniques for inferring evolutionary histories in cancer, from the use of chromosomal rearrangements to tumor phylogenetics approaches; examines problems in phylogenetic networks, including questions relating to discrete mathematics, and issues of statistical estimation; highlights how evolution can provide a framework within which to understand comparative and functional genomics; provides an introduction to Integer Linear Programming and its use in computational biology, including its use for solving the Traveling Salesman Problem.Offering an invaluable source of insights for computer scientists, applied mathematicians, and statisticians, this illuminating volume will also prove useful for graduate courses on computational biology and bioinformatics.
Reviews / Votes
"The book is mainly aimed at researchers with pre-existing knowledge of phylogenetics and computational approaches related to it (e.g. graph theory). The numerous examples make this collection of chapters comprehensible for undergraduate, graduate and postgraduate researchers from computer science, mathematics and biology; the extensive set of references that accompany every chapter recommend the book as a reliable starting point for further studies." (Irina Ioana Mohorianu, zbMATH 1429.92003, 2020)
Series
Edition
Language
Place of publication
Publishing group
Springer International Publishing
Target group
Primary & secondary/elementary & high school
Illustrations
63 farbige Abbildungen, 50 s/w Abbildungen
XXV, 410 p. 113 illus., 63 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 29 mm
Weight
ISBN-13
978-3-030-10836-6 (9783030108366)
DOI
10.1007/978-3-030-10837-3
Schweitzer Classification
Dr. Tandy Warnow
is the Founder Professor of Computer Science at the University of Illinois at Urbana-Champaign, where she is also an affiliate in the departments of Mathematics, Statistics, Bioengineering, Electrical and Computer Engineering, Animal Biology, Entomology, and Plant Biology. Tandy received her PhD in Mathematics in 1991 at UC Berkeley under the direction of Gene Lawler, and did postdoctoral training with Simon Tavaré and Michael Waterman at USC. Her research combines computer science, statistics, and discrete mathematics, focusing on developing improved models and algorithms for reconstructing complex and large-scale evolutionary histories in biology and historical linguistics. She has published more than 160 papers and one textbook, graduated 11 PhD students, and has 5 current PhD students. Her awards include the NSF Young Investigator Award (1994), the David and Lucile Packard Foundation Award (1996), a Radcliffe Institute Fellowship (2006), and the John Simon Guggenheim Foundation Fellowship (2011). She was elected a Fellow of the Association for Computing Machinery (ACM) in 2015 and of the International Society for Computational Biology (ISCB) in 2017. Warnow succeeded Bernard Moret as the director of the NSF-funded CIPRES (Cyber-Infrastructure for Phylogenetic Research) project, whose goal was "To provide the computational infrastructure needed to reconstruct phylogenies for millions of taxa".
Introduction: A Biography of Bernard Moret.- A Review of Approaches for Optimizing Phylogenetic Likelihood Calculations.- Numerical Optimization Techniques in Maximum Likelihood Tree Inference.- High-Performance Phylogenetic Inference.- Hands-On Introduction to Sequence-Length Requirements in Phylogenetics.- Gene Family Evolution - An Algorithmic Framework.- Divide-and-Conquer Tree Estimation: Opportunities and Challenges.- Taxonomic Supertree Construction with
incertae sedis
Taxa.- Evolutionary Rate Change and the Transformation from Additive to Ultrametric: Modal Similarity of Orthologs in Fish and Flower Phylogenomics.- Ancestral Genome Reconstruction.- Genome Rearrangement Problems with Single and Multiple Gene Copies: A Review.- Computational Models for Cancer Phylogenetics.- Clusters, Trees and Phylogenetic Network Classes.- Advances in Computational Methods for Phylogenetic Networks in the Presenceof Hybridization.- A Perspective on Comparative and Functional Genomics.- Integer Linear Programming in Computational Biology: Overview of ILP, and New Results for Traveling Salesman Problems in Biology.
