Author: Olga Valba Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Complex organization is found in many biological systems. For example, biopolymers could possess very hierarchic structure, which provides their functional peculiarity. Understating such, complex organization allows describing biological phenomena and predicting molecule functions. Besides, we can try to characterize the specific phenomenon by some probabilistic quantities (variances, means, etc), assuming the primary biopolymer structure to be randomly formed according to some statistical distribution. Such a formulation is oriented toward evolutionary problems.Artificially constructed biological network is another common object of statistical physics with rich functional properties. A behavior of cells is a consequence of complex interactions between its numerous components, such as DNA, RNA, proteins and small molecules. Cells use signaling pathways and regulatory mechanisms to coordinate multiple processes, allowing them to respond and to adapt to changing environment. Recent theoretical advances allow us to describe cellular network structure using graph concepts to reveal the principal organizational features shared with numerous non-biological networks.The aim of this thesis is to develop bunch of methods for studying statistical and dynamic objects of complex architecture and, in particular, scale-free structures, which have no characteristic spatial and/or time scale. For such systems, the use of standard mathematical methods, relying on the average behavior of the whole system, is often incorrect or useless, while a detailed many-body description is almost hopeless because of the combinatorial complexity of the problem. Here we focus on two problems.The first part addresses to statistical analysis of random biopolymers. Apart from the evolutionary context, our studies cover more general problems of planar topology appeared in description of various systems, ranging from gauge theory to biophysics. We investigate analytically and numerically a phase transition of a generic planar matching problem, from the regime, where almost all the vertices are paired, to the situation, where a finite fraction of them remains unmatched.The second part of this work focus on statistical properties of networks. We demonstrate the possibility to define co-expression gene clusters within a network context from their specific motif distribution signatures. We also show how a method based on the shortest path function (SPF) can be applied to gene interactions sub-networks of co-expression gene clusters, to efficiently predict novel regulatory transcription factors (TFs). The biological significance of this method by applying it on groups of genes with a shared regulatory locus, found by genetic genomics, is presented. Finally, we discuss formation of stable patters of motifs in networks under selective evolution in context of creation of islands of "superfamilies".
Author: Eli Ben-Naim Publisher: Springer Science & Business Media ISBN: 9783540223542 Category : Science Languages : en Pages : 548
Book Description
This volume is devoted to the applications of techniques from statistical physics to the characterization and modeling of complex networks. The first two parts of the book concern theory and modeling of networks, the last two parts survey applications to a wide variety of natural and artificial networks. The tutorial reviews that form this book are aimed at students and newcomers to the field, and will also constitute a modern and comprehensive reference for experts. To this aim, all contributions have been carefully peer-reviewed not only for scientific content but also for self-consistency and readability.
Author: Romualdo Pastor-Satorras Publisher: Springer Science & Business Media ISBN: 9783540403722 Category : Science Languages : en Pages : 232
Book Description
Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.
Author: Konstantin Avrachenkov Publisher: ISBN: 9781638280507 Category : Computers Languages : en Pages : 0
Book Description
This book is a general introduction to the statistical analysis of networks, and can serve both as a research monograph and as a textbook. Numerous fundamental tools and concepts needed for the analysis of networks are presented, such as network modeling, community detection, graph-based semi-supervised learning and sampling in networks. The description of these concepts is self-contained, with both theoretical justifications and applications provided for the presented algorithms. Researchers, including postgraduate students, working in the area of network science, complex network analysis, or social network analysis, will find up-to-date statistical methods relevant to their research tasks. This book can also serve as textbook material for courses related to the statistical approach to the analysis of complex networks. In general, the chapters are fairly independent and self-supporting, and the book could be used for course composition "à la carte". Nevertheless, Chapter 2 is needed to a certain degree for all parts of the book. It is also recommended to read Chapter 4 before reading Chapters 5 and 6, but this is not absolutely necessary. Reading Chapter 3 can also be helpful before reading Chapters 5 and 7. As prerequisites for reading this book, a basic knowledge in probability, linear algebra and elementary notions of graph theory is advised. Appendices describing required notions from the above mentioned disciplines have been added to help readers gain further understanding.
Author: Scott T. Weidman Publisher: National Academies Press ISBN: 0309101050 Category : Computers Languages : en Pages : 470
Book Description
A large number of biological, physical, and social systems contain complex networks. Knowledge about how these networks operate is critical for advancing a more general understanding of network behavior. To this end, each of these disciplines has created different kinds of statistical theory for inference on network data. To help stimulate further progress in the field of statistical inference on network data, the NRC sponsored a workshop that brought together researchers who are dealing with network data in different contexts. This book - which is available on CD only - contains the text of the 18 workshop presentations. The presentations focused on five major areas of research: network models, dynamic networks, data and measurement on networks, robustness and fragility of networks, and visualization and scalability of networks.
Author: Albert Diaz-Guilera Publisher: ISBN: 9788354044949 Category : Biophysics Languages : en Pages : 0
Book Description
Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.
Author: Mark C. Leake Publisher: CRC Press ISBN: 100380652X Category : Medical Languages : en Pages : 457
Book Description
Biophysics: Tools and Techniques for the Physics of Life covers the experimental, theoretical, and computational tools and techniques of biophysics. It addresses the purpose, science, and application of all physical science instrumentation, theoretical analysis, and biophysical computational methods used in current research labs. The book first presents the historical background, concepts, and motivation for using a physical science toolbox to understand biology. It then familiarizes undergraduate students from the physical sciences with essential biological knowledge. The text subsequently focuses on experimental biophysical techniques that primarily detect biological components or measure/control biological forces. The author describes the science and application of key tools used in imaging, detection, general quantitation, and biomolecular interaction studies, which span multiple length and time scales of biological processes both in the test tube and in the living organism. Moving on to theoretical and computational biophysics tools, the book presents analytical mathematical methods and numerical simulation approaches for tackling challenging biological questions including exam-style questions at the end of each chapter as well as step-by-step solved exercises. It concludes with a discussion of the future of this exciting field. Future innovators will need to be trained in multidisciplinary science to be successful in industry, academia, and government support agencies. Addressing this challenge, this textbook educates future leaders on the development and application of novel physical science approaches to solve complex problems linked to biological questions. Features: Provides the full, modern physical science toolbox of experimental, theoretical, and computational techniques, such as bulk ensemble methods, single-molecule tools, live-cell and test tube methods, pencil-on-paper theory approaches, and simulations. Incorporates worked examples for the most popular physical science tools by providing full diagrams and a summary of the science involved in the application of the tool. Reinforces the understanding of key concepts and biological questions. A solutions manual is available upon qualifying course adoption.
Author: Eric D. Kolaczyk Publisher: Springer ISBN: 9781441927767 Category : Computers Languages : en Pages : 0
Book Description
In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
Author: Olga Valba
Author: Eli Ben-Naim
Author: Romualdo Pastor-Satorras
Author: Romualdo Pastor-Satorras
Author: Konstantin Avrachenkov
Author: Scott T. Weidman
Author: Albert Diaz-Guilera
Author: Hocine Cherifi
Author: Mark C. Leake
Author: Eric D. Kolaczyk