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Author: Matthias Dehmer
Publisher: CRC Press
Published: 2014-10-27
Total Pages: 528
ISBN-13: 1466584521
DOWNLOAD EBOOK →The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications presents and demonstrates existing and novel methods for analyzing graphs quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical technique
Author: Matthias Dehmer
Publisher: CRC Press
Published: 2014-10-27
Total Pages: 530
ISBN-13: 1466584513
DOWNLOAD EBOOK →The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications presents and demonstrates existing and novel methods for analyzing graphs quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical techniques, this book covers a wide range of quantitative-graph theoretical concepts and methods, including those pertaining to real and random graphs such as: Comparative approaches (graph similarity or distance) Graph measures to characterize graphs quantitatively Applications of graph measures in social network analysis and other disciplines Metrical properties of graphs and measures Mathematical properties of quantitative methods or measures in graph theory Network complexity measures and other topological indices Quantitative approaches to graphs using machine learning (e.g., clustering) Graph measures and statistics Information-theoretic methods to analyze graphs quantitatively (e.g., entropy) Through its broad coverage, Quantitative Graph Theory: Mathematical Foundations and Applications fills a gap in the contemporary literature of discrete and applied mathematics, computer science, systems biology, and related disciplines. It is intended for researchers as well as graduate and advanced undergraduate students in the fields of mathematics, computer science, mathematical chemistry, cheminformatics, physics, bioinformatics, and systems biology.
Author: Matthias Dehmer
Publisher: John Wiley & Sons
Published: 2017-09-12
Total Pages: 298
ISBN-13: 3527339094
DOWNLOAD EBOOK →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.
Author: Courtney Brown
Publisher: SAGE
Published: 2008
Total Pages: 105
ISBN-13: 1412941091
DOWNLOAD EBOOK →This book describes an easily applied language of mathematical modeling that uses boxes and arrows to develop very sophisticated, algebraic statements of social and political phenomena.
Author: Mark R.T. Dale
Publisher: Cambridge University Press
Published: 2017-11-09
Total Pages: 355
ISBN-13: 110708931X
DOWNLOAD EBOOK →This book clearly describes the many applications of graph theory to ecological questions, providing instruction and encouragement to researchers.
Author: Ruggero Gramatica
Publisher:
Published: 2015
Total Pages: 428
ISBN-13:
DOWNLOAD EBOOK →I have shown how it is possible to fully capture the dynamical aspects of the phenomena under investigation by identifying clusters carrying influential information and tracking them over time. By computing graphbased statistics over such clusters I turn the evolution of textual information into a mathematically well-defined, multivariate time series, where each time series encodes the evolution of particular structural, topological and semantic properties of the set of concepts previously extracted and filtered. Eventually iv : : an autoregressive model with vectorial exogenous inputs is defined, which linearly mixes previous values of an index with the evolution of other time series induced by the semantic information in the graph. The methodology briefly described above concludes the contribution of my research work in the field of Complex Systems and it has been instrumental in successfully defining a graph-theoretical model for the study of drug repurposing [1 J and the construction of a framework for the analysis of financial and economic unstructured data (see chapter 6).
Author: Edward R. Tufte
Publisher:
Published: 2001-01-01
Total Pages: 197
ISBN-13: 9780961392147
DOWNLOAD EBOOK →Graphical practice. Theory of data graphics.
Author: Danail Bonchev
Publisher: Taylor & Francis
Published: 1992
Total Pages: 294
ISBN-13: 9780856265150
DOWNLOAD EBOOK →Building on the background of graph theory provided in the first volume of the series, presents a detailed examination of the role of graph theory in the study of chemical kinetics, reaction mechanisms, and quantitative structure-activity relations, in a manner useful to theoretical chemists. Among the topics are heterogeneous catalytic reactions, the classification and coding of chemical reaction mechanisms, the mechanist's description of chemical processes as it relates to aromaticity, and using operator networks to interpret evolutionary interrelations between chemical entities. Annotation copyright by Book News, Inc., Portland, OR
Author: Mark R. T. Dale
Publisher: Cambridge University Press
Published: 2021-04-15
Total Pages: 250
ISBN-13: 1108632971
DOWNLOAD EBOOK →Network thinking and network analysis are rapidly expanding features of ecological research. Network analysis of ecological systems include representations and modelling of the interactions in an ecosystem, in which species or factors are joined by pairwise connections. This book provides an overview of ecological network analysis including generating processes, the relationship between structure and dynamic function, and statistics and models for these networks. Starting with a general introduction to the composition of networks and their characteristics, it includes details on such topics as measures of network complexity, applications of spectral graph theory, how best to include indirect species interactions, and multilayer, multiplex and multilevel networks. Graduate students and researchers who want to develop and understand ecological networks in their research will find this volume inspiring and helpful. Detailed guidance to those already working in network ecology but looking for advice is also included.
Author: Eric D. Kolaczyk
Publisher: Springer
Published: 2014-05-22
Total Pages: 214
ISBN-13: 1493909835
DOWNLOAD EBOOK →Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).
