Topological data analysis for genomics and evolution : topology in biology / Raúl Rabadán, Andrew J. Blumberg.

Call Number	570.285
Author	Rabadán, Raúl, author.
Title	Topological data analysis for genomics and evolution : topology in biology / Raúl Rabadán, Andrew J. Blumberg.
Physical Description	1 online resource (xvii, 501 pages) : digital, PDF file(s).
Notes	Title from publisher's bibliographic system (viewed on 21 Nov 2019).
Summary	Biology has entered the age of Big Data. A technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce comparisons of shape to a comparison of algebraic invariants, such as numbers, which are typically easier to work with. Topological data analysis is a rapidly developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer, and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolutionary biology as well as mathematicians interested in applied topology.
Added Author	Blumberg, Andrew J., author.
Subject	Bioinformatics Mathematical models. COMPUTATIONAL BIOLOGY. MATHEMATICAL ANALYSIS.
Multimedia	https://doi.org/10.1017/9781316671665

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Summary	Biology has entered the age of Big Data. A technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce comparisons of shape to a comparison of algebraic invariants, such as numbers, which are typically easier to work with. Topological data analysis is a rapidly developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer, and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolutionary biology as well as mathematicians interested in applied topology.
Notes	Title from publisher's bibliographic system (viewed on 21 Nov 2019).
Subject	Bioinformatics Mathematical models. COMPUTATIONAL BIOLOGY. MATHEMATICAL ANALYSIS.
Multimedia	https://doi.org/10.1017/9781316671665