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Bioinformatics and Phylogenetics - Seminal Contributions of Bernard Moret (Hardcover, 1st ed. 2019)
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Bioinformatics and Phylogenetics - Seminal Contributions of Bernard Moret (Hardcover, 1st ed. 2019)
Series: Computational Biology, 29
Expected to ship within 10 - 15 working days
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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.
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