Bioinformatics and Phylogenetics

1. Front Matter

   Pages i-xxv

   PDF

2. A Review of Approaches for Optimizing Phylogenetic Likelihood Calculations

   • Alexandros Stamatakis

   Pages 1-19

3. Numerical Optimization Techniques in Maximum Likelihood Tree Inference

   • Stéphane Guindon, Olivier Gascuel

   Pages 21-38

4. High-Performance Phylogenetic Inference

   • David A. Bader, Kamesh Madduri

   Pages 39-45

5. Hands-on Introduction to Sequence-Length Requirements in Phylogenetics

   • Sébastien Roch

   Pages 47-86

6. Gene Family Evolution—An Algorithmic Framework

   • Nadia El-Mabrouk, Emmanuel Noutahi

   Pages 87-119

7. Divide-and-Conquer Tree Estimation: Opportunities and Challenges

   • Tandy Warnow

   Pages 121-150

8. Taxonomic Supertree Construction with Incertae sedis Taxa

   • Benjamin D. Redelings, Mark T. Holder

   Pages 151-173

9. Evolutionary Rate Change and the Transformation from Additive to Ultrametric: Modal Similarity of Orthologs in Fish and Flower Phylogenomics

   • Daniella Santos Muñoz, Eric Lam, David Sankoff

   Pages 175-192

10. Ancestral Genome Reconstruction

    • Jijun Tang

    Pages 193-203

11. Genome Rearrangement Problems with Single and Multiple Gene Copies: A Review

    • Ron Zeira, Ron Shamir

    Pages 205-241

12. Computational Models for Cancer Phylogenetics

    • Russell Schwartz

    Pages 243-275

13. Clusters, Trees, and Phylogenetic Network Classes

    • Louxin Zhang

    Pages 277-315

14. Advances in Computational Methods for Phylogenetic Networks in the Presence of Hybridization

    • R. A. Leo Elworth, Huw A. Ogilvie, Jiafan Zhu, Luay Nakhleh

    Pages 317-360

15. A Perspective on Comparative and Functional Genomics

    • Daniel Doerr, Jens Stoye

    Pages 361-372

16. Integer Linear Programming in Computational Biology: Overview of ILP, and New Results for Traveling Salesman Problems in Biology

    • Dan Gusfield

    Pages 373-404

17. Back Matter

    Pages 405-410

    PDF

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.

• Bioinformatics
• Phylogenetics
• Plant genomics
• Genetic simulation
• Cell modelling

“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)

• University of Illinois at Urbana-Champaign, Urbana, USA

  Tandy Warnow

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”.

Policies and ethics