This book reviews recent advances in the emerging field of computational network biology with special emphasis on comparative network analysis and network module detection. The chapters in this volume are contributed by leading international researchers in computational network biology and offer in-depth insight on the latest techniques in network alignment, network clustering, and network module detection. Chapters discuss the advantages of the respective techniques and present the current challenges and open problems in the field. Recent Advances in Biological Network Analysis: Comparative Network Analysis and Network Module Detection will serve as a great resource for graduate students, academics, and researchers who are currently working in areas relevant to computational network biology or wish to learn more about the field. Data scientists whose work involves the analysis of graphs, networks, and other types of data with topological structure or relations can also benefit from the book's insights.

An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research.

Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource. - Presents recent advances in biological network analysis, combining Graph Theory, Graph Analysis, and various network models - Discusses three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN) and Human Brain Connectomes - Includes a discussion of various graph theoretic and data analytics approaches

This book constitutes selected papers of the ​Third International Conference on Data Science, Medicine and Bioinformatics, IDMB 2019, held in Nanning, China, in June 2019. The 19 full papers and 1 short paper were carefully reviewed and selected from 93 submissions. The papers are organized according to the following topical sections: business data science: fintech, management, and analytics.- health and biological data science.- novel data science theory and applications.

The convergence of biology and computer science was initially motivated by the need to organize and process a growing number of biological observations resulting from rapid advances in experimental techniques. Today, however, close collaboration between biologists, biochemists, medical researchers, and computer scientists has also generated remarkable benefits for the field of computer science. Systemic Approaches in Bioinformatics and Computational Systems Biology: Recent Advances presents new techniques that have resulted from the application of computer science methods to the organization and interpretation of biological data. The book covers three subject areas: bioinformatics, computational biology, and computational systems biology. It focuses on recent, systemic approaches in computer science and mathematics that have been used to model, simulate, and more generally, experiment with biological phenomena at any scale.

The first edition of this book was greeted with broad interest from readers en gaged in various disciplines of biophysics. I received many stimulating and en couraging responses, however, some of the book's reviewers wanted to stress the fact that an extensive literature of network theory was not included or reported in the book. But the main aspect of the book is intended to be substantive rather than methodical: networks simply serve as a remedy for doing some first steps in analysing and modelling complex biological systems. For an advanced stage in the investigation of a particular system it may be appropriate to replace the pheno menological network method by more detailed techniques like statistical equations or computer simulations. According to this intention, the second edition of the book has been enlarged by further biological examples for network analysis, not by more network theory. There is a completely new section on a network model for photoreception. For this section I am obliged to J. Tiedge who did most of the detailed calculation and to my colleague Professor Stieve with whom we have had a very fruitful cooperation. Also I would like to mention that this work has been sponsored by the "Deutsche Forschungsgemei nschaft" i n the "Sonderforschungsberei ch 160". Recent results for excitable systems represented by feedback networks have also been included in the second edition, especially for limit cycle networks.

“Recent Advances in Rice Research” is an interdisciplinary book dealing with diverse topics related to recent developments in rice research. The book discusses the latest research activities in the field of hybrid rice, various metabolites produced in rice and its biology, stress studies, and strategies to combat various biotic and abiotic stresses as well as rice economics, value addition, and product development. The book is written by an international team of researchers from all over the globe sharing their results in the field of rice research. I am hopeful that the scientific information available in this book will provide advanced knowledge for rice researchers, students, life scientists, and interested readers on some of the latest developments in rice research.