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Item Details
Title: MATHEMATICAL FOUNDATIONS AND APPLICATIONS OF GRAPH ENTROPY
By: Matthias Dehmer (Editor), Frank Emmert-Streib (Editor), Xueliang Li (Editor)
Format: Hardback

List price: £126.95
Our price: £104.73
Discount:
17.5% off
You save: £22.22
ISBN 10: 3527339094
ISBN 13: 9783527339099
Availability: Usually dispatched within 1-3 weeks.
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Stock: Currently 0 available
Publisher: JOHN WILEY AND SONS LTD
Pub. date: 15 September, 2016
Series: Quantitative and Network Biology (VCH)
Pages: 296
Description: This latest volume in the successful Network Biology series presents current methods for determining the entropy of networks, covering the analysis of mathematical properties of methods as well as applications in areas ranging from applied mathematics to chemical graph theory.
Synopsis: 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.
Publication: UK
Imprint: Wiley-VCH Verlag GmbH
Returns: Returnable
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ADVANCES IN NETWORK COMPLEXITY
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ANALYSIS OF MICROARRAY DATA
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APPLICATIONS OF STATISTICAL AND MACHINE LEARNING METHODS IN BIOINFORMATICS (PB)
APPLIED STATISTICS FOR NETWORK BIOLOGY
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BIG DATA OF COMPLEX NETWORKS
BIG DATA OF COMPLEX NETWORKS
BIG DATA OF COMPLEX NETWORKS
BIG DATA OF COMPLEX NETWORKS (HB)
COMPUTATIONAL NETWORK ANALYSIS WITH R
COMPUTATIONAL NETWORK ANALYSIS WITH R
COMPUTATIONAL NETWORK ANALYSIS WITH R
COMPUTATIONAL NETWORK ANALYSIS WITH R (HB)
COMPUTATIONAL NETWORK THEORY
COMPUTATIONAL NETWORK THEORY
COMPUTATIONAL NETWORK THEORY
COMPUTATIONAL NETWORK THEORY (HB)
DISCRETE GEOMETRY, COMBINATORICS AND GRAPH THEORY (PB)
ELEMENTS OF DATA SCIENCE, MACHINE LEARNING, AND ARTIFICIAL INTELLIGENCE USING R (HB)
FOAM FRACTIONATION
FOAM FRACTIONATION (HB)
FRONTIERS IN DATA SCIENCE
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GENERALIZED CONNECTIVITY OF GRAPHS (PB)
GRAPH ENERGY (HB)
GRAPH ENERGY (PB)
GRAPH POLYNOMIALS
GRAPH POLYNOMIALS (HB)
INFORMATION THEORY AND STATISTICAL LEARNING (HB)
INFORMATION THEORY AND STATISTICAL LEARNING (PB)
MATHEMATICAL FOUNDATIONS AND APPLICATIONS OF GRAPH ENTROPY
MATHEMATICAL FOUNDATIONS AND APPLICATIONS OF GRAPH ENTROPY
MATHEMATICAL FOUNDATIONS AND APPLICATIONS OF GRAPH ENTROPY
MATHEMATICAL FOUNDATIONS OF DATA SCIENCE USING R
MATHEMATICAL FOUNDATIONS OF DATA SCIENCE USING R (HB)
MEDICAL BIOSTATISTICS FOR COMPLEX DISEASES
MEDICAL BIOSTATISTICS FOR COMPLEX DISEASES (HB)
PROPERLY COLORED CONNECTIVITY OF GRAPHS (PB)
QUANTITATIVE GRAPH THEORY
QUANTITATIVE GRAPH THEORY (HB)
RAINBOW CONNECTIONS OF GRAPHS (PB)
STATISTICAL AND MACHINE LEARNING APPROACHES FOR NETWORK ANALYSIS
STATISTICAL AND MACHINE LEARNING APPROACHES FOR NETWORK ANALYSIS
STATISTICAL AND MACHINE LEARNING APPROACHES FOR NETWORK ANALYSIS
STATISTICAL AND MACHINE LEARNING APPROACHES FOR NETWORK ANALYSIS
STATISTICAL AND MACHINE LEARNING APPROACHES FOR NETWORK ANALYSIS (HB)
STATISTICAL DIAGNOSTICS FOR CANCER
STATISTICAL DIAGNOSTICS FOR CANCER
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STATISTICAL DIAGNOSTICS FOR CANCER (HB)
STATISTICAL MODELLING OF MOLECULAR DESCRIPTORS IN QSAR/QSPR
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STRUCTURAL ANALYSIS OF COMPLEX NETWORKS
STRUCTURAL ANALYSIS OF COMPLEX NETWORKS (HB)
STRUKTURELLE ANALYSE WEB-BASIERTER DOKUMENTE (PB)
TOWARDS AN INFORMATION THEORY OF COMPLEX NETWORKS (HB)

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