Huge Mechanisms in Devices Biology: Huge Information Mining, Network Modeling, and Genome-Vast Information Identification points out massive mechanisms of units biology by program identification and massive information mining strategies making use of designs of biological units. Devices biology is currently going through revolutionary changes in reaction to the integration of potent technologies. Faced with a massive quantity of out there…
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Author : Bor-Sen Chen
Genre : Medical
Summary : 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
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Author : Sangdun Choi
Genre : Science
Summary : This book provides an introductory text for undergraduate and graduate students who are interested in comprehensive biological systems. The authors offer a broad overview of the field using key examples and typical approaches to experimental design. The volume begins with an introduction to systems biology and then details experimental omics tools. Other sections introduce the reader to challenging computational approaches. The final sections provide ideas for theoretical and modeling optimization in systemic biological researches. The book is an indispensable resource, providing a first glimpse into the state-of-the-art in systems biology.
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Author : Edda Klipp
Genre : Medical
Summary : This advanced textbook is tailored for an introductory course in Systems Biology and is well-suited for biologists as well as engineers and computer scientists. It comes with student-friendly reading lists and a companion website featuring a short exam prep version of the book and educational modeling programs. The text is written in an easily accessible style and includes numerous worked examples and study questions in each chapter. For this edition, a section on medical systems biology has been included.
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Author : Shigetada Nakanishi
Genre : Science
Summary : Biological signaling pathways dynamically interact with one another to form complex information networks intracellularly, intercellularly, and eventually at the level of the organism. Biology and medicine have conventionally focused on identification and characterization of functional elements in biological signaling pathways. Recently, research in this field has pursued a new approach, systems biology, to understand the dynamics, complexity, and physiological functions of the biological signaling networks. Instead of reductionistic analyses or large-scale studies of biomolecules piece by piece, systems biology emphasizes the need for interdisciplinary methods and analysis of the regulation and operation of information networks at the systems level. The contributors to this book are leading researchers in the rising field of systems biology. Readers will find not only the most recent advances in research, but also the latest information about interdisciplinary methods and related topics.
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Author : Osbaldo Resendis-Antonio
Genre :
Summary : Since the discovery of the Warburg effect in the 1920s cancer has been tightly associated with the genetic and metabolic state of the cell. One of the hallmarks of cancer is the alteration of the cellular metabolism in order to promote proliferation and undermine cellular defense mechanisms such as apoptosis or detection by the immune system. However, the strategies by which this is achieved in different cancers and sometimes even in different patients of the same cancer is very heterogeneous, which hinders the design of general treatment options. Recently, there has been an ongoing effort to study this phenomenon on a genomic scale in order to understand the causality underlying the disease. Hence, current “omics” technologies have contributed to identify and monitor different biological pieces at different biological levels, such as genes, proteins or metabolites. These technological capacities have provided us with vast amounts of clinical data where a single patient may often give rise to various tissue samples, each of them being characterized in detail by genomescale data on the sequence, expression, proteome and metabolome level. Data with such detail poses the imminent problem of extracting meaningful interpretations and translating them into specific treatment options. To this purpose, Systems Biology provides a set of promising computational tools in order to decipher the mechanisms driving a healthy cell’s metabolism into a cancerous one. However, this enterprise requires bridging the gap between large data resources, mathematical analysis and modeling specifically designed to work with the available data. This is by no means trivial and requires high levels of communication and adaptation between the experimental and theoretical side of research.
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Author : Ross Carlson
Genre : Science
Summary : Modern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled “Methods in Computational Biology”, is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections: • Reviews of Computational Methods • Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels • The Interface of Biotic and Abiotic Processes • Processing of Large Data Sets for Enhanced Analysis • Parameter Optimization and Measurement
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Author : Shailza Singh
Genre : Science
Summary : This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.
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Author : Anupam Nath Jha
Genre : Science
Summary : This book explores the intricate world of livestock sciences and production through the lens of systems biology. Offering a comprehensive exploration of both fundamental and advanced aspects, it unearths the potential of systems biology in the realm of livestock. The book presents 13 edited chapters on cutting-edge knowledge about systems biology and omics technology, showcasing genomics, transcriptomics, proteomics, metabolomics, and more. It illuminates the role of systems biology in livestock and disease management. Readers will learn about power of technologies that merge computational biology, nanobiotechnology, artificial intelligence, and single-cell sequencing. Each chapter is written by scientific experts and includes references for further reading. The book covers 4 key themes: Introduction to Systems Biology in Livestock Science: Uncover the foundation of integrating systems biology with omics data for animal scientists. Multi-scale Modeling Techniques: Explore how multi-scale modeling is shaping the future of system biology. Livestock Viral Diseases: Gain insights into how systems biology is revolutionizing our understanding of livestock viral diseases. Single Cell RNA-Sequencing: Understand the potential of this advanced technique in studying livestock animals at a cellular level. This book is a timely resource for students and researchers, offering a pathway to comprehend the crucial role systems biology plays in sustainable livestock production and management.
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Author : Bor-Sen Chen
Genre : Science
Summary : 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.
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Author : OECD
Genre :
Summary : This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.