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Mathematical Foundations And Applications Of Graph Entropy 1st Edition Matthias Dehmer

  • SKU: BELL-22041952
Mathematical Foundations And Applications Of Graph Entropy 1st Edition Matthias Dehmer
$ 31.00 $ 45.00 (-31%)

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Mathematical Foundations And Applications Of Graph Entropy 1st Edition Matthias Dehmer instant download after payment.

Publisher: Wiley, Wiley-VCH
File Extension: PDF
File size: 4.83 MB
Pages: 299
Author: Matthias Dehmer, Frank Emmert-Streib, Zengqiang Chen, Xueliang Li, Yongtang Shi (Editors)
ISBN: 9783527339099, 9783527693221, 9783527693245, 3527339094, 352769322X, 3527693246, B01J6V1WXC
Language: English
Year: 2016
Edition: 1
Volume: 6

Product desciption

Mathematical Foundations And Applications Of Graph Entropy 1st Edition Matthias Dehmer by Matthias Dehmer, Frank Emmert-streib, Zengqiang Chen, Xueliang Li, Yongtang Shi (editors) 9783527339099, 9783527693221, 9783527693245, 3527339094, 352769322X, 3527693246, B01J6V1WXC instant download after payment.

Main subject categories: • Mathematics - Graph theory • Mathematics - Graph entropy • Mathematical statistics • Probability • Biology • Mathematical biology

This latest addition to the successful Network Biology series presents current methods for determining the entropy of networks, making it the first to cover the recently established Quantitative Graph Theory.

An excellent international team of editors and contributors provides an up-to-date outlook for the field, covering a broad range of graph entropy-related concepts and methods. The topics range from analyzing mathematical properties of methods right up to applying them in real-life areas.

Filling a gap in the contemporary literature this is an invaluable reference for a number of disciplines, including mathematicians, computer scientists, computational biologists, and structural chemists.

The book introduces to the reader a number of cutting-edge statistical methods which can be used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.

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