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" Fundamentals of network biology / "
WenJun Zhang (Sun Yat-sen University, China).
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BL
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| Record Number
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856162
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| Main Entry
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Zhang, WenJun,1963-
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| Title & Author
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Fundamentals of network biology /\ WenJun Zhang (Sun Yat-sen University, China).
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| Publication Statement
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London ;Hackensack, NJ :: World Scientific Publishing Europe Ltd,, [2018]
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, ©2018
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1 online resource
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| ISBN
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1786345099
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: 1786345102
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: 9781786345097
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: 9781786345103
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1786345080
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9781786345080
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Intro; Contents; Preface; About the Author; Acknowledgments; Part 1 Mathematical Fundamentals; 1 Fundamentals of Graph Theory; 1.1 Definitions and Concepts; 1.1.1 Finite graph and infinite graph; 1.1.2 Simple graph and planar graph; 1.1.3 Subgraph, proper subgraph, spanning subgraph, complementary graph; 1.1.4 Complete graph and m-order complete graph; 1.1.5 Edge sequence, edge train, and path; 1.1.6 Connected graph, unconnected graph, and connected components; 1.1.7 Separable graph, inseparable graph, bipartite graph, and disjoint graph; 1.1.8 Degree of vertex
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1.1.9 Directed graph and undirected graph; 1.1.10 Cutset and association set; 1.1.11 Tree and tree branch; 1.1.12 Isomorphism; 1.2 Topological Definition of Graph; 1.2.1 Homotopy, homotopy type; 1.2.2 Connectedness; 1.2.2.1 Connectedness; 1.2.2.2 Path connectedness; 1.2.3 Simplicial complex, polyhedron, graph; 1.2.3.1 Simplex; 1.2.3.2 Simplicial complex; 1.2.3.3 Polyhedron; 1.2.3.4 Abstract complex, graph; 2 Graph Algorithms; 2.1 Matrix Representation of Graphs; 2.1.1 Undirected graph; 2.1.1.1 Incidence matrix; 2.1.1.2 Circuit matrix; 2.1.1.3 Cutset matrix; 2.1.2 Directed graph
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2.1.2.1 Incidence matrix; 2.1.2.2 Adjacency matrix; 2.1.2.3 Circuit matrix; 2.1.2.4 Cutset matrix; 2.1.2.5 Walk matrix and reachability matrix; 2.2 Computer Storage of Graph; 2.3 Graph Algorithms; 2.3.1 Tree algorithms; 2.3.1.1 DFS algorithm; 2.3.1.2 Minty's algorithm; 2.3.1.3 The shortest tree algorithm; 2.3.2 Connectedness algorithms; 2.3.2.1 Connectedness; 2.3.2.2 Vertex connectivity; 2.3.2.3 Connectedness of directed graph; 2.3.2.4 Block, cut vertex, bridge; 2.3.3 The shortest path; 2.3.3.1 Floyd algorithm; 2.3.3.2 Dijkstra algorithm; 2.3.4 Circuit algorithm
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2.3.4.1 Paton's fundamental circuit finding algorithm; 2.3.4.2 Chan's circuit matrix algorithm; 2.3.5 Matching problem; 2.3.5.1 Maximum matching; 2.3.5.2 Optimum matching; 3 Fundamentals of Network Theory; 3.1 Network Topology; 3.1.1 Cellular topology; 3.1.2 Bus topology; 3.1.3 Tree topology; 3.1.4 Star topology; 3.1.5 Ring topology; 3.1.6 Mesh topology; 3.2 Random and Complex Networks; 3.2.1 Random network; 3.2.2 Complex networks; 3.2.2.1 Measurement of complex networks; 3.2.2.2 Generation and calculation of complex networks; 3.3 Network Analysis; 3.4 Basic Algorithms; 3.4.1 Maximum flow
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3.4.2 Minimum cost flow; 4 Other Fundamentals; 4.1 Bayes' Rule; 4.1.1 Model selection; 4.1.2 Bayesian learning; 4.2 Linear Regression; 4.2.1 Single-variable linear regression; 4.2.2 Multiple-variable linear regression; 4.3 Randomization, Bootstrap, and Monte Carlo Methods; 4.3.1 Random numbers; 4.3.1.1 General random numbers; 4.3.1.2 Probability distributions and random numbers; 4.3.1.3 Multivariable random numbers; 4.3.2 Randomization-based data partition; 4.3.2.1 Cross-validation; 4.3.2.2 Jackknife method; 4.3.3 Bootstrap method; 4.3.4 Monte Carlo method; 4.4 Stochastic Process
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| Abstract
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"As the first comprehensive title on network biology, this book covers a wide range of subjects including scientific fundamentals (graphs, networks, etc) of network biology, construction and analysis of biological networks, methods for identifying crucial nodes in biological networks, link prediction, flow analysis, network dynamics, evolution, simulation and control, ecological networks, social networks, molecular and cellular networks, network pharmacology and network toxicology, big data analytics, and more. Across 12 parts and 26 chapters, with Matlab codes provided for most models and algorithms, this self-contained title provides an in-depth and complete insight on network biology. It is a valuable read for high-level undergraduates and postgraduates in the areas of biology, ecology, environmental sciences, medical science, computational science, applied mathematics, and social science."--
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| Subject
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Bioinformatics.
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Biometry-- Data processing.
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Systems biology-- Methodology.
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Bioinformatics.
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Biometry-- Data processing.
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NATURE-- Reference.
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SCIENCE-- Life Sciences-- Biology.
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SCIENCE-- Life Sciences-- General.
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| Dewey Classification
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570.1/5195
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| LC Classification
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QH323.5.Z45 2018
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