Integrative Computational Systems Biology Approaches In Immunology And Medicine

Technological advances in generated molecular and cell biological data are transforming biomedical research. Sequencing, multi-omics and imaging technologies are likely to have deep impact on the future of medical practice. In parallel to technological developments, methodologies to gather, integrate, visualize and analyze heterogeneous and large-scale data sets are needed to develop new approaches for diagnosis, prognosis and therapy. Systems Medicine: Integrative, Qualitative and Computational Approaches is an innovative, interdisciplinary and integrative approach that extends the concept of systems biology and the unprecedented insights that computational methods and mathematical modeling offer of the interactions and network behavior of complex biological systems, to novel clinically relevant applications for the design of more successful prognostic, diagnostic and therapeutic approaches. This 3 volume work features 132 entries from renowned experts in the fields and covers the tools, methods, algorithms and data analysis workflows used for integrating and analyzing multi-dimensional data routinely generated in clinical settings with the aim of providing medical practitioners with robust clinical decision support systems. Importantly the work delves into the applications of systems medicine in areas such as tumor systems biology, metabolic and cardiovascular diseases as well as immunology and infectious diseases amongst others. This is a fundamental resource for biomedical students and researchers as well as medical practitioners who need to need to adopt advances in computational tools and methods into the clinical practice. Encyclopedic coverage: ‘one-stop’ resource for access to information written by world-leading scholars in the field of Systems Biology and Systems Medicine, with easy cross-referencing of related articles to promote understanding and further research Authoritative: the whole work is authored and edited by recognized experts in the field, with a range of different expertise, ensuring a high quality standard Digitally innovative: Hyperlinked references and further readings, cross-references and diagrams/images will allow readers to easily navigate a wealth of information

This second edition expands upon and updates the vital research covered in its predecessor, by presenting state-of-the-art multidisciplinary and systems-oriented approaches to complex diseases arising from and driven by the acute inflammatory response. The chapters in this volume provide an introduction to different types of computational modeling, and how these methods can be applied to specific inflammatory diseases, with a focus on providing readers a roadmap for integrating advanced mathematical and computational techniques with traditional experimental methods. In this second edition, we cover both well-established and emerging modeling methods, especially state-of-the-art machine learning approaches and the integration of data-driven and mechanistic modeling. This volume introduces the concept of Model-based Precision Medicine as an alternative approach to the current view of Precision Medicine, based on leveraging mechanistic computational modeling to decrease cost while increasing the information value of the data being obtained. By presenting the role of computational modeling as an integrated component of the research process, Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine offers a window into the recent past, the present, and the future of computationally-augmented biomedical research.

Immuno Systems Biology aims to study the immune system in the more integrated manner on how cells and molecules participate at different system levels to the immune function. Through this book Kumar Selvarajoo introduces to physicists, chemists, computer scientists, biologists and immunologists the idea of an integrated approach to the understanding of mammalian immune system. Geared towards a researcher with limited immunological and computational analytical experience, the book provides a broad overview to the subject and some instruction in basic computational, theoretical and experimental approaches. The book links complex immunological processes with computational analysis and emphasizes the importance of immunology to the mammalian system.

Praise for Computational Systems BiologyApproaches in Cancer Research: "Complex concepts are written clearly and with informative illustrations and useful links. The book is enjoyable to read yet provides sufficient depth to serve as a valuable resource for both students and faculty." — Trey Ideker, Professor of Medicine, UC Xan Diego, School of Medicine "This volume is attractive because it addresses important and timely topics for research and teaching on computational methods in cancer research. It covers a broad variety of approaches, exposes recent innovations in computational methods, and provides acces to source code and to dedicated interactive web sites." — Yves Moreau, Department of Electrical Engineering, SysBioSys Centre for Computational Systems Biology, University of Leuven With the availability of massive amounts of data in biology, the need for advanced computational tools and techniques is becoming increasingly important and key in understanding biology in disease and healthy states. This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. The book provides an important reference and teaching material in the field of computational biology in general and cancer systems biology in particular. The book presents a list of modern approaches in systems biology with application to cancer research and beyond. It is structured in a didactic form such that the idea of each approach can easily be grasped from the short text and self-explanatory figures. The coverage of topics is diverse: from pathway resources, through methods for data analysis and single data analysis to drug response predictors, classifiers and image analysis using machine learning and artificial intelligence approaches. Features Up to date using a wide range of approaches Applicationexample in each chapter Online resources with useful applications’

This volume addresses the latest state-of-the-art systems biology-oriented approaches that--driven by big data and bioinformatics--are utilized by Computational Systems Biology, an interdisciplinary field that bridges experimental tools with computational tools to tackle complex questions at the frontiers of knowledge in medicine and biotechnology. The chapters in this book are organized into six parts: systems biology of the genome, epigenome, and redox proteome; metabolic networks; aging and longevity; systems biology of diseases; spatiotemporal patterns of rhythms, morphogenesis, and complex dynamics; and genome scale metabolic modeling in biotechnology. In every chapter, readers will find varied methodological approaches applied at different levels, from molecular, cellular, organ to organisms, genome to phenome, and health and disease. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics; criteria utilized for applying specific methodologies; lists of the necessary materials, reagents, software, databases, algorithms, mathematical models, and dedicated analytical procedures; step-by-step, readily reproducible laboratory, bioinformatics, and computational protocols all delivered in didactic and clear style and abundantly illustrated with express case studies and tutorials; and tips on troubleshooting and advice for achieving reproducibility while avoiding mistakes and misinterpretations. The overarching goal driving this volume is to excite the expert and stimulate the newcomer to the field of Computational Systems Biology. Cutting-edge and authoritative, Computational Systems Biology in Medicine and Biotechnology: Methods and Protocols is a valuable resource for pre- and post-graduate students in medicine and biotechnology, and in diverse areas ranging from microbiology to cellular and organismal biology, as well as computational and experimental biologists, and researchers interested in utilizing comprehensive systems biology oriented methods.

First, systems biology is an inter-disciplinary approach, requiring the combined talents of biologists, mathematicians, and computer scientists. Second, systems biology is holistic, with the goal of obtaining a comprehensive understanding of the workings of biological systems. This is achieved through the acquisition of massive amounts of data by high-throughput technologies—oligonucleotide microarrays, mass spectrometry, and next-generation sequencing—and the analysis of this data through sophisticated mathematical algorithms. It is perhaps the use of mathematics, to integrate abundant and diverse types of data and to generate models of interconnected molecular networks, that best characterizes systems biology.

This volume guides readers through the field of systems medicine by defining the terminology, and describing how established computational methods form bioinformatics and systems biology can be taken forward to an integrative systems medicine approach. Chapters provide an outlook on the role that systems medicine may or should play in various medical fields, and describe different facets of the systems medicine approach in action. Ultimately it introduces tools, resources and methodologies from bioinformatics and systems biology, and how to apply these in a systems medicine project. Written for the Methods in Molecular Biology series, chapters include introductions to their respective topics, and discuss experimental and computational approaches, methods, and tools that should be considered for a successful systems medicine project. Systems Medicine aims to motivate and provide guidance for collaborations across disciplines to tackle today's challenges related to human health and well-being.