Boolean Networks As Predictive Models Of Emergent Biological Behaviors
Download Boolean Networks As Predictive Models Of Emergent Biological Behaviors full books in PDF, epub, and Kindle. Read online free Boolean Networks As Predictive Models Of Emergent Biological Behaviors ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : Jordan C. Rozum |
Publisher | : Cambridge University Press |
Total Pages | : 118 |
Release | : 2024-03-28 |
Genre | : Science |
ISBN | : 1009292943 |
Interacting biological systems at all organizational levels display emergent behavior. Modeling these systems is made challenging by the number and variety of biological components and interactions – from molecules in gene regulatory networks to species in ecological networks – and the often-incomplete state of system knowledge, such as the unknown values of kinetic parameters for biochemical reactions. Boolean networks have emerged as a powerful tool for modeling these systems. This Element provides a methodological overview of Boolean network models of biological systems. After a brief introduction, the authors describe the process of building, analyzing, and validating a Boolean model. They then present the use of the model to make predictions about the system's response to perturbations and about how to control its behavior. The Element emphasizes the interplay between structural and dynamical properties of Boolean networks and illustrates them in three case studies from disparate levels of biological organization.
Author | : Jordan C. Rozum |
Publisher | : Cambridge University Press |
Total Pages | : 0 |
Release | : 2024-03-31 |
Genre | : Science |
ISBN | : 9781009292962 |
This Element shows interacting biological systems at all organizational levels display emergent behavior. Modeling these systems is made challenging by the number and variety of biological components and interactions and the often-incomplete state of system knowledge. Boolean networks have emerged as a powerful tool for modeling these systems. The authors provide a methodological overview of Boolean network models of biological systems. After a brief introduction, they describe the process of building, analyzing, and validating a Boolean model. The authors then present the use of the model to make predictions about the system's response to perturbations and about how to control its behavior. The Element emphasizes the interplay between structural and dynamical properties of Boolean networks and illustrates them in three case studies from disparate levels of biological organization.
Author | : |
Publisher | : Elsevier |
Total Pages | : 4876 |
Release | : 2019-07-17 |
Genre | : Science |
ISBN | : 0444640479 |
Comprehensive Biotechnology, Third Edition, Six Volume Set unifies, in a single source, a huge amount of information in this growing field. The book covers scientific fundamentals, along with engineering considerations and applications in industry, agriculture, medicine, the environment and socio-economics, including the related government regulatory overviews. This new edition builds on the solid basis provided by previous editions, incorporating all recent advances in the field since the second edition was published in 2011. Offers researchers a one-stop shop for information on the subject of biotechnology Provides in-depth treatment of relevant topics from recognized authorities, including the contributions of a Nobel laureate Presents the perspective of researchers in different fields, such as biochemistry, agriculture, engineering, biomedicine and environmental science
Author | : Ignacio Rojas |
Publisher | : Springer Nature |
Total Pages | : 387 |
Release | : 2024 |
Genre | : Bioinformatics |
ISBN | : 3031646363 |
Zusammenfassung: This volume constitutes the proceedings of the 11th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 15-17, 2022. The 54 full papers were carefully reviewed and selected from 148 submissions. They were organized in the following topical sections: Healthcare and Diseases, Machine Learning in Bioinformatics, New Advances in Deep Learning in Bioinformatics and Biomedicine, Novel Methodologies and Applications in Bioinformatics and Biomedicine
Author | : Adriana Compagnoni |
Publisher | : Springer |
Total Pages | : 219 |
Release | : 2019-07-23 |
Genre | : Computers |
ISBN | : 3030242021 |
This book constitutes the refereed conference proceedings of the 11th International Conference on Bio-Inspired Information and Communications Technologies, held in Pittsburgh, PA, USA, in March 2019. The 13 revised full papers and 2 short papers were selected from 29 submissions. Past iterations of the conference have attracted contributions in Direct Bioinspiration (physical biological materials and systems used within technology) as well as Indirect Bioinspiration (biological principles, processes and mechanisms used within the design and application of technology). This year, the scope has expanded to include a third thrust: Foundational Bioinspiration (bioinspired aspects of game theory, evolution, information theory, and philosophy of science).
Author | : Raina Robeva |
Publisher | : Academic Press |
Total Pages | : 383 |
Release | : 2015-05-09 |
Genre | : Mathematics |
ISBN | : 0128012714 |
Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems. Each chapter begins with a question from modern biology, followed by the description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set. This book is appropriate for mathematics courses such as finite mathematics, discrete structures, linear algebra, abstract/modern algebra, graph theory, probability, bioinformatics, statistics, biostatistics, and modeling, as well as for biology courses such as genetics, cell and molecular biology, biochemistry, ecology, and evolution. - Examines significant questions in modern biology and their mathematical treatments - Presents important mathematical concepts and tools in the context of essential biology - Features material of interest to students in both mathematics and biology - Presents chapters in modular format so coverage need not follow the Table of Contents - Introduces projects appropriate for undergraduate research - Utilizes freely accessible software for visualization, simulation, and analysis in modern biology - Requires no calculus as a prerequisite - Provides a complete Solutions Manual - Features a companion website with supplementary resources
Author | : Ilya Shmulevich |
Publisher | : SIAM |
Total Pages | : 276 |
Release | : 2010-01-21 |
Genre | : Mathematics |
ISBN | : 0898716926 |
The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.
Author | : |
Publisher | : Elsevier |
Total Pages | : 4609 |
Release | : 2017-06-03 |
Genre | : Technology & Engineering |
ISBN | : 0128032014 |
Comprehensive Medicinal Chemistry III, Eight Volume Set provides a contemporary and forward-looking critical analysis and summary of recent developments, emerging trends, and recently identified new areas where medicinal chemistry is having an impact. The discipline of medicinal chemistry continues to evolve as it adapts to new opportunities and strives to solve new challenges. These include drug targeting, biomolecular therapeutics, development of chemical biology tools, data collection and analysis, in silico models as predictors for biological properties, identification and validation of new targets, approaches to quantify target engagement, new methods for synthesis of drug candidates such as green chemistry, development of novel scaffolds for drug discovery, and the role of regulatory agencies in drug discovery. Reviews the strategies, technologies, principles, and applications of modern medicinal chemistry Provides a global and current perspective of today's drug discovery process and discusses the major therapeutic classes and targets Includes a unique collection of case studies and personal assays reviewing the discovery and development of key drugs
Author | : Darren D.R. Flower |
Publisher | : Springer |
Total Pages | : 201 |
Release | : 2009-10-03 |
Genre | : Medical |
ISBN | : 1441905405 |
Like many words, the term “immunomics” equates to different ideas contingent on context. For a brief span, immunomics meant the study of the Immunome, of which there were, in turn, several different definitions. A now largely defunct meaning rendered the Immunome as the set of antigenic peptides or immunogenic proteins within a single microorganism – be that virus, bacteria, fungus, or parasite – or microbial population, or antigenic or allergenic proteins and peptides derived from the environment as a whole, containing also proteins from eukaryotic sources. However, times have changed and the meaning of immunomics has also changed. Other newer definitions of the Immunome have come to focus on the plethora of immunological receptors and accessory molecules that comprise the host immune arsenal. Today, Immunomics or immunogenomics is now most often used as a synonym for high-throughput genome-based immunology. This is the study of aspects of the immune system using high-throughput techniques within a conc- tual landscape borne of both clinical and biophysical thinking.
Author | : Matteo Barberis |
Publisher | : Frontiers Media SA |
Total Pages | : 340 |
Release | : 2019-08-16 |
Genre | : |
ISBN | : 2889459837 |
Mathematical models have become invaluable tools for understanding the intricate dynamic behavior of complex biochemical and biological systems. Among computational strategies, logical modeling has been recently gaining interest as an alternative approach to address network dynamics. Due to its advantages, including scalability and independence of kinetic parameters, the logical modeling framework is becoming increasingly popular to study the dynamics of highly interconnected systems, such as cell cycle progression, T cell differentiation and gene regulation. Novel tools and standards have been developed to increase the interoperability of logical models, which can now be employ to respond a variety of biological questions. This Research Topic brings together the most recent and cutting-edge approaches in the area of logical modeling including, among others, novel biological applications, software development and model analysis techniques.