Bioinformatics and phylogenetics : seminal contributions of Bernard Moret
- 其他作者：
- 其他題名：
- Computational biology ;
- 出版： Cham : Springer International Publishing :Imprint: Springer
- 叢書名： Computational biology,volume 29
- 主題： Computational biology. , Bioinformatics. , Phylogeny. , Computational Biology/Bioinformatics. , Plant Genetics and Genomics. , Simulation and Modeling. , Bioinformatics.
- ISBN： 9783030108373 (electronic bk.) 、 9783030108366 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
- 內容註: 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 Presence of 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.
- 摘要註: 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. 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 Ma
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讀者標籤：
- 系統號： 005450176 | 機讀編目格式
館藏資訊
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.