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Author: Rinku Sharma
Publisher: Frontiers Media SA
ISBN: 2832531679
Category : Science
Languages : en
Pages : 121
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Book Description
The biological complexity essentially includes and involves processes that are mediated through explicitly non-linear interactions that are often typically entangled in nature. These comprise a myriad of interactions among a vast number of entities such as genes, proteins, metabolites, and species, widely varying in scale. These interactions render biological systems across spatial and temporal scales as complex adaptive systems having features like: self-organisation, modularity, emergence, non-linear interactions, collective response and adaptation. The theory of complex networks offers an appropriate formal framework for modelling such complex systems. The enormous wealth of biological data generated by high-throughput techniques, as also through empirical investigations can be analysed using the aforementioned formal framework to obtain important insights into biological complexity.The concept of networks can be used:1) to explore the relationships between entities resulting in network generation; 2) to guide the analytic procedure based on existing network(s) as prior knowledge; and 3) to analyze the prior network(s) regarding their topology and attributes. Complex networks, being ubiquitous, permeate the biological systems across spatial and temporal scales. The objective of this collection is to highlight some very salient features of such inherent complexity in biological systems by adopting a network theoretic perspective. The anticipated pay-off is obtaining a deeper insight explicitly into the systems-level interactions and the emergent complex behaviour of the systems. Also, investigating the propulsive forces which lend various networks with akin topological characteristics that would help to merge vivid information related to various molecular interactions into a single framework, thereby permitting a structural perspective of the cellular dynamics.The application may include – exploring the disease/environmental stress response and trait mechanism using different omics platforms, candidate gene discovery and validation, network-guided discovery and deployment of omics approaches in biology; modern genetic improvement methods for delivering genes in addition to high throughput and precise phenotyping methodologies, exploring the disease/environmental stress response mechanism, marker re-prioritization, network-guided biomarker discovery etc.
Author: Rinku Sharma
Publisher: Frontiers Media SA
ISBN: 2832531679
Category : Science
Languages : en
Pages : 121
Get Book Here
Book Description
The biological complexity essentially includes and involves processes that are mediated through explicitly non-linear interactions that are often typically entangled in nature. These comprise a myriad of interactions among a vast number of entities such as genes, proteins, metabolites, and species, widely varying in scale. These interactions render biological systems across spatial and temporal scales as complex adaptive systems having features like: self-organisation, modularity, emergence, non-linear interactions, collective response and adaptation. The theory of complex networks offers an appropriate formal framework for modelling such complex systems. The enormous wealth of biological data generated by high-throughput techniques, as also through empirical investigations can be analysed using the aforementioned formal framework to obtain important insights into biological complexity.The concept of networks can be used:1) to explore the relationships between entities resulting in network generation; 2) to guide the analytic procedure based on existing network(s) as prior knowledge; and 3) to analyze the prior network(s) regarding their topology and attributes. Complex networks, being ubiquitous, permeate the biological systems across spatial and temporal scales. The objective of this collection is to highlight some very salient features of such inherent complexity in biological systems by adopting a network theoretic perspective. The anticipated pay-off is obtaining a deeper insight explicitly into the systems-level interactions and the emergent complex behaviour of the systems. Also, investigating the propulsive forces which lend various networks with akin topological characteristics that would help to merge vivid information related to various molecular interactions into a single framework, thereby permitting a structural perspective of the cellular dynamics.The application may include – exploring the disease/environmental stress response and trait mechanism using different omics platforms, candidate gene discovery and validation, network-guided discovery and deployment of omics approaches in biology; modern genetic improvement methods for delivering genes in addition to high throughput and precise phenotyping methodologies, exploring the disease/environmental stress response mechanism, marker re-prioritization, network-guided biomarker discovery etc.
Author: Pietro Hiram Guzzi
Publisher: Elsevier
ISBN: 0128193514
Category : Science
Languages : en
Pages : 212
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Book Description
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
Author: Uri Alon
Publisher: CRC Press
ISBN: 1000001326
Category : Mathematics
Languages : en
Pages : 343
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Book Description
Praise for the first edition: ... superb, beautifully written and organized work that takes an engineering approach to systems biology. Alon provides nicely written appendices to explain the basic mathematical and biological concepts clearly and succinctly without interfering with the main text. He starts with a mathematical description of transcriptional activation and then describes some basic transcription-network motifs (patterns) that can be combined to form larger networks. – Nature [This text deserves] serious attention from any quantitative scientist who hopes to learn about modern biology ... It assumes no prior knowledge of or even interest in biology ... One final aspect that must be mentioned is the wonderful set of exercises that accompany each chapter. ... Alon’s book should become a standard part of the training of graduate students. – Physics Today Written for students and researchers, the second edition of this best-selling textbook continues to offer a clear presentation of design principles that govern the structure and behavior of biological systems. It highlights simple, recurring circuit elements that make up the regulation of cells and tissues. Rigorously classroom-tested, this edition includes new chapters on exciting advances made in the last decade. Features: Includes seven new chapters The new edition has 189 exercises, the previous edition had 66 Offers new examples relevant to human physiology and disease The book website including course videos can be found here: https://www.weizmann.ac.il/mcb/UriAlon/introduction-systems-biology-design-principles-biological-circuits.
Author: Mark Buchanan
Publisher: Cambridge University Press
ISBN: 0521882737
Category : Science
Languages : en
Pages : 282
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Book Description
Key introductory text for graduate students and researchers in physics, biology and biochemistry.
Author: Wenjun Zhang
Publisher: World Scientific
ISBN: 1786345102
Category : Medical
Languages : en
Pages : 568
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Book Description
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.
Author: Luonan Chen
Publisher: John Wiley & Sons
ISBN: 9780470488058
Category : Computers
Languages : en
Pages : 416
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Book Description
Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.
Author: Nataša Pržulj
Publisher: Cambridge University Press
ISBN: 1108432239
Category : Language Arts & Disciplines
Languages : en
Pages : 647
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Book Description
Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.
Author: Narsis A. Kiani
Publisher: Cambridge University Press
ISBN: 1108428878
Category : Computers
Languages : en
Pages : 215
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Book Description
Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.
Author: Alberto Marin-Sanguino
Publisher: Frontiers Media SA
ISBN: 2889456838
Category :
Languages : en
Pages : 216
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Book Description
If biology in the 20th century was characterized by an explosion of new technologies and experimental methods, that of the 21st has seen an equally exuberant proliferation of mathematical and computational methods that attempt to systematize and explain the abundance of available data. As we live through the consolidation of a new paradigm where experimental data goes hand in hand with computational analysis, we contemplate the challenge of fusing these two aspects of the new biology into a consistent theoretical framework. Whether systems biology will survive as a field or be washed away by the tides of future fads will ultimately depend on its success to achieve this type of synthesis. The famous quote attributed to Kurt Lewin comes to mind: "there is nothing more practical than a good theory". This book presents a wide assortment of articles on systems biology in an attempt to capture the variety of current methods in systems biology and show how they can help to find answers to the challenges of modern biology.
Author: Björn H. Junker
Publisher: John Wiley & Sons
ISBN: 1118209915
Category : Computers
Languages : en
Pages : 278
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Book Description
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.
