Big Mechanisms in Systems Biology: Big Data Mining, Network Modeling, and Genome-Wide Data Identification explains big mechanisms of systems biology by system identification and big data mining methods using models of biological systems. Systems biology is currently undergoing revolutionary changes in response to the integration of powerful technologies. Faced with a large volume of available literature, complicated mechanisms, small prior knowledge, few classes on the topics, and causal and mechanistic language, this is an ideal resource. This book addresses system immunity, regulation, infection, aging, evolution, and carcinogenesis, which are complicated biological systems with inconsistent findings in existing resources. These inconsistencies may reflect the underlying biology time-varying systems and signal transduction events that are often context-dependent, which raises a significant problem for mechanistic modeling since it is not clear which genes/proteins to include in models or experimental measurements. The book is a valuable resource for bioinformaticians and members of several areas of the biomedical field who are interested in an in-depth understanding on how to process and apply great amounts of biological data to improve research. Written in a didactic manner in order to explain how to investigate Big Mechanisms by big data mining and system identification Provides more than 140 diagrams to illustrate Big Mechanism in systems biology Presents worked examples in each chapter

This book presents a novel molecular description for understanding the regulatory mechanisms behind the autonomy and self-organization in biological systems. Chapters focus on defining and explaining the regulatory molecular mechanisms behind different aspects of autonomy and self-organization in the sense of autonomous coding, data processing, structure (mass) formation and energy production in a biological system. Subsequent chapters discuss the cross-talk among mechanisms of energy, and mass and information, transformation in biological systems. Other chapters focus on applications regarding therapeutic approaches in regenerative medicine. Molecular Mechanisms of Autonomy in Biological Systems is an indispensable resource for scientists and researchers in regenerative medicine, stem cell biology, molecular biology, tissue engineering, developmental biology, biochemistry, biophysics, bioinformatics, as well as big data sciences, complexity and soft computing.

This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling. Logical information flow aids understanding of basic building blocks of life through disease phenotypes Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.

The first comprehensive single-authored textbook on genome-scale models and the bottom-up approach to systems biology.

A brilliant young scientist introduces us to the fascinating field that is changing our understanding of how the body works and the way we can approach healing. SYSTEMATIC is the first book to introduce general readers to systems biology, which is improving medical treatments and our understanding of living things. In traditional bottom-up biology, a biologist might spend years studying how a single protein works, but systems biology studies how networks of those proteins work together--how they promote health and how to remedy the situation when the system isn't functioning properly. Breakthroughs in systems biology became possible only when powerful computer technology enabled researchers to process massive amounts of data to study complete systems, and has led to progress in the study of gene regulation and inheritance, cancer drugs personalized to an individual's genetically unique tumor, insights into how the brain works, and the discovery that the bacteria and other microbes that live in the gut may drive malnutrition and obesity. Systems biology is allowing us to understand more complex phenomena than ever before. In accessible prose, SYSTEMATIC sheds light not only on how systems within the body work, but also on how research is yielding new kinds of remedies that enhance and harness the body's own defenses.

This new book takes an in-depth look at the emerging and prospective field of computational biology and bioinformatics, which possesses the ability to analyze large accumulated biological data collected from sequence analysis of proteins and genes and cell population with an aim to make new predictions pertaining to drug discovery and new biology. The book explains the basic methodology associated with a bioinformatics and computational approach in drug designing. It then goes on to cover the implementation of computational programming, bioinformatics, pharmacophore modeling, biotechnological techniques, and pharmaceutical chemistry in designing drugs. The major advantage of intervention of computer language or programming is to cut down the number of steps and costs in the field of drug designing, reducing the repeating steps and saving time in screening the potent component for drug or vaccine designing. The book describes algorithms used for drug designing and the use of machine learning and AI in drug delivery and disease diagnosis, which are valuable in clinical decision-making. The implementation of robotics in different diseases like stroke, cancer, COVID-19, etc. is also addressed. Topics include machine learning, AI, databases in drug design, molecular docking, bioinformatics tools, target-based drug design, and immunoinformatics, chemoinformatics, and nanoinformatics in drug design. Drug repurposing in drug design in general as well as for specific diseases, including cancer, Alzheimer’s disease, tuberculosis, COVID-19, etc., is also addressed in depth.

The objective of this book is to present the strategies employed by living organisms on a molecular level and to help understand the basics of Systems Biology. Its content is organized in a way to meet the exponential growth in the volume of biological knowledge, and the need for a multidisciplinary approach in the practice of teaching modern biology. For this reason, the whole material is divided into five chapters, each devoted to a fundamental concept: Structure-Function, Energy, Information, Regulation and Interrelationships. The book describes generic mechanisms which occur in biology and promotes a simulation-based approach to the subject of Systems Biology. The use of basic knowledge as the background for presenting biological problems obligates the teachers to deal with generalized phenomena comprising the ever increasing volume of teaching materials. This book is intended for biologists and is informative for specialists in the areas of computer science, robotics and engineering.