This teaching monograph on systems approaches to cancer research and clinical applications provides a unique synthesis, by world-class scientists and doctors, of laboratory, computational, and clinical methods, thereby establishing the foundations for major advances not possible with current methods. Specifically, the book: 1) Sets the stage by describing the basis of systems biology and bioinformatics approaches, and the clinical background of cancer in a systems context; 2) Summarizes the laboratory, clinical, data systems analysis and bioinformatics tools, along with infrastructure and resources required; 3) Demonstrates the application of these tools to cancer research; 4) Extends these tools and methods to clinical diagnosis, drug development and treatment applications; and 5) Finishes by exploring longer term perspectives and providing conclusions. This book reviews the state-of-the-art, and goes beyond into new applications. It is written and highly referenced as a textbook and practical guide aimed at students, academics, doctors, clinicians, industrialists and managers in cancer research and therapeutic applications. Ideally, it will set the stage for integration of available knowledge to optimize communication between basic and clinical researchers involved in the ultimate fight against cancer, whatever the field of specific interest, whatever the area of activity within translational research.

Translational Bioinformatics and Systems Biology Methods for Personalized Medicine introduces integrative approaches in translational bioinformatics and systems biology to support the practice of personalized, precision, predictive, preventive, and participatory medicine. Through the description of important cutting-edge technologies in bioinformatics and systems biology, readers may gain an essential understanding of state-of-the-art methodologies. The book discusses topics such as the challenges and tasks in translational bioinformatics; pharmacogenomics, systems biology, and personalized medicine; and the applicability of translational bioinformatics for biomarker discovery, epigenomics, and molecular dynamics. It also discusses data integration and mining, immunoinformatics, and neuroinformatics. With broad coverage of both basic scientific and clinical applications, this book is suitable for a wide range of readers who may not be scientists but who are also interested in the practice of personalized medicine. Introduces integrative approaches in translational bioinformatics and systems biology to support the practice of personalized, precision, predictive, preventive, and participatory medicine Presents a problem-solving oriented methodology to deal with practical problems in various applications Covers both basic scientific and clinical applications in order to enhance the collaboration between researchers and clinicians Brings integrative and multidisciplinary approaches to bridge the gaps among various knowledge domains in the field

Cancer Immunology is intended as an up-to-date, clinically relevant review of cancer immunology and immunotherapy. This volume is focused on immunopathology of cancers. The interactions between cancerous cells and various components of the innate and adaptive immune system are fully described. The principal focus, however, is very much on clinical aspects, the aim being to educate clinicians in the clinical implications of the most recent research and new developments in the field. Over the past decade, understanding of the interactions between the immune system and cancerous cells has increased markedly, leading to the development of combinatorial immunotherapeutic strategies to combat cancer. This translational, clinically oriented book will be of special value to clinical immunologists, hematologists and oncologists.

This book includes original research articles and reviews to update readers on the state of the art systems approach to not only discover novel diagnostic and prognostic biomarkers for several cancer types, but also evaluate methodologies to map out important genomic signatures. In addition, therapeutic targets and drug repurposing have been emphasized for a variety of cancer types. In particular, new and established researchers who desire to learn about cancer systems biology and why it is possibly the leading front to a personalized medicine approach will enjoy reading this book.

If biology in the 20th century was characterized by an explosion of new technologies and experimental methods, that of the 21st has seen an equally exuberant proliferation of mathematical and computational methods that attempt to systematize and explain the abundance of available data. As we live through the consolidation of a new paradigm where experimental data goes hand in hand with computational analysis, we contemplate the challenge of fusing these two aspects of the new biology into a consistent theoretical framework. Whether systems biology will survive as a field or be washed away by the tides of future fads will ultimately depend on its success to achieve this type of synthesis. The famous quote attributed to Kurt Lewin comes to mind: "there is nothing more practical than a good theory". This book presents a wide assortment of articles on systems biology in an attempt to capture the variety of current methods in systems biology and show how they can help to find answers to the challenges of modern biology.

The cost of drug development is increasing, and investment returns are decreasing. The number of drugs approved by FDA is in decline in terms of the number of new molecular entities (NMEs). Amongst the reasons noted for this are the adverse side effects and reduced efficiency of many of the potential compounds. This is a problem both for the pharmaceutical industry and for those suffering from diseases for which there are no or few available treatments. Advances in computational chemistry, computer science, structural biology and molecular biology have all contributed to improved drug design strategies and reduced the time taken for drug discovery. By interfacing cheminformatics and bioinformatics with systems biology we can create a powerful tool for understanding the mechanisms of patho-physiological systems and identifying lead molecules for various diseases. This integration of drug design approaches can also play a crucial role in the prediction and rationalization of drug effects and side effects, improving safety and efficacy and leading to better approval rates. Addressing the lack of knowledge on the fundamental aspects of the various computational tools for drug discovery, this book is a compilation of recent bioinformatics and cheminformatics approaches, and their integration with systems biology. Written primarily for researchers and academics in chem- and bioinformatics, it may also be a useful resource for advanced-level students.

Systems biology is the inevitable outcome of long years of knowledge acquisition and data accumulation. The aim of systems biology is to integrate in a seamless way all existing knowledge in interconnected disciplines, stretching from modern biomedical research to physics, chemistry, and mathematics. The main integration tool of such complex biomedical systems is via computational and mathematical modeling. In this direction, a series of state-of-the-art computer science techniques are used, namely, data mining and fusion, machine learning, and deep learning all under the prism of big data. All in all, systems biology is at the arrowhead of modern and state-of-the-art biomedical research by attempting to address key biological questions describing holistically complex biological systems.

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 book offers an overall review, applying systems engineering and architecture approaches, of the design, optimization, operation and results of leading fusion experiments. These approaches provide a unified means of evaluating reactor design. Methodologies are developed for more coherent construction or evaluation of fusion devices, associated experiments and operating procedures. The main focus is on tokamaks, with almost all machines and their important results being integrated into a systems design space. Case studies focus on DIII-D, TCV, JET, WEST, the fusion reactor prototype ITER and the EU DEMO concept. Stellarator, Mirror and Laser inertial confinement experiments are similarly analysed, including reactor implications of breakeven at NIF. The book examines the engineering and physics design and optimization process for each machine, analysing their performance and major results achieved, thus establishing a basis for the improvement of future machines. The reader will gain a broad historical and up-to-date perspective of the status of nuclear fusion research from both an engineering and physics point of view. Explanations are given of the computational tools needed to design and operate successful experiments and reactor-relevant machines. This book is aimed at both graduate students and practitioners of nuclear fusion science and engineering, as well as those specializing in other fields demanding large and integrated experimental equipment. Systems engineers will obtain valuable insights into fusion applications. References are given to associated complex mathematical derivations, which are beyond the scope of this book. The general reader interested in nuclear fusion will find here an accessible summary of the current state of nuclear fusion.