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Sensing in Nature (Hardcover)

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ISBN 10: 1461417031 / ISBN 13: 9781461417033
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Hardcover. Biological systems are an emerging discipline that may provide integrative tools by assembling the hierarchy of interactions among genes, proteins and molecular networks involved in sensor.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 316 pages. 0.771. Bookseller Inventory # 9781461417033

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Bibliographic Details

Title: Sensing in Nature (Hardcover)

Binding: Hardcover

Book Condition:New

Edition: 2012th.

About this title

Synopsis:

Biological systems are an emerging discipline that may provide integrative tools by assembling the hierarchy of interactions among genes, proteins and molecular networks involved in sensory systems. The aim of this volume is to provide a picture, as complete as possible, of the current state of knowledge of sensory systems in nature. The presentation in this book lies at the intersection of evolutionary biology, cell and molecular biology, physiology and genetics. Sensing in Nature is written by a distinguished panel of specialists and is intended to be read by biologists, students, scientific investigators and the medical community.

From the Back Cover:

The increasing availability of molecular and genetic databases coupled with the growing power of computers gives biologists opportunities to address new issues, such as the patterns of molecular evolution, and re-assess old ones, such as the role of adaptation in species diversification.In the second edition, the book continues to integrate a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists' data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments. The second edition is completely updated, covering the full gamut of R packages for this area that have been introduced  to the market since its previous publication five years ago. There is also  a new chapter on the simulation of evolutionary data.  Graduate students and researchers in evolutionary biology can use this book as a reference for data analyses, whereas researchers in bioinformatics interested in evolutionary analyses will learn how to implement these methods in R. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered: manipulation of phylogenetic data, phylogeny estimation, tree drawing, phylogenetic comparative methods, and estimation of ancestral characters. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.

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