Computational Immunology: Models and Toolsencompasses the methodological framework and application of cutting-edge tools and techniques to study immunological processes at a systems level, along with the concept of multi-scale modeling.
The book's emphasis is on selected cases studies and application of the most updated technologies in computational modeling, discussing topics such as computational modeling and its usage in immunological research, bioinformatics infrastructure, ODE based modeling, agent based modeling, and high performance computing, data analytics, and multiscale modeling.
There are also modeling exercises using recent tools and models which lead the readers to a thorough comprehension and applicability.
The book is a valuable resource for immunologists, computational biologists, bioinformaticians, biotechnologists, and computer scientists, as well as all those who wish to broaden their knowledge in systems modeling.Offers case studies with different levels of complexityProvides a detailed view on cutting-edge tools for modeling that are useful to experimentalists with limited computational skillsExplores the usage of simulation for hypothesis generation, helping the reader to understand the most valuable points on experimental setting
The topic of "the visual" has become increasingly important as advances in technology have led to multi-media and multi-modal representations, and extended the range and scope of visual representation and interpretation in our lives. Under this broad heading there are many different perspectives and approaches, from across the entire spectrum of human knolwedge and activity.
The editors and authors of this book aim to break down cross-disciplinary barriers, by bringing together people working in a wide variety of disciplines where visual representations and interpretations are exploited. Contributions come from researchers actively investigating visual representations and interpretations in a wide variety of areas, including art history, biology, clinical science, cognitive science, computer science, design, engineering, linguistics, mathematics, philosophy, physics, psychology, and sociology.
The book provides a forum for wide-ranging and multi-disciplinary contributions on visual representations and interpretations.
* Contributors include researchers actively investigating visual representations and interpretations
* Content spans a wide variety of areas including but not limited to biology, sociology, and computer science
* Discusses how new technology has affected "the visual" representation of information
Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your data
"Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author
Multidisciplinary Approaches to Theory in Medicine will therefore be integrative across a broad spectrum of fields within medicine. To achieve this the chapters will be associated with others in a number of meaningful ways. Each chapter will share a number of points of contact that will include at least two of the following:Similar biomedical area (e.g., immunity, neuroscience, endocrinology, pathology, oncology, haematology, ...)Similar multidisciplinary theoretical contexts (e.g., modelling, analysis, description, visualization, complex systems, ...)Similar multidisciplinary medical issues and questions (e.g., clinical practice, decision making, informatics, ...)Uniquely explores role of interdisciplinary exchange in the development and expansion of medical theoryTimely and insightful essays on the growth and development of medical theories from some of the world's top clinicians and medical researchers, including Werner Arber, Frank Vertosick, and David WeatherallAssembles diverse perspectives on medicine and physiology from biology, statistics, ethics, computer science, philosophy, historyUniquely illuminates the social and historical processes through which theoretical research translates into clinical practiceReveals the growing role of technology, especially computational modelling, in changing the nature of Western medicine
C-ImmSim is best viewed as a collection of models in a single program. It incorporates the principal core facts of today’s immunological knowledge, such as the diversity of specific elements, MHC restriction, clonal selection, thymic education of T cells, antigen processing and presentation (both the cytosolic and endocytic pathways are implemented), cell-cell cooperation, homeostasis of cells created by the bone marrow, hyper mutation of antibodies, maturation of the cellular and humoral response, and memory. Besides, an antigen can represent a bacterium, a virus, or an allergen or a tumor cell. C-ImmSim has been recently customized to simulate the HIV-1 infection. Moreover, it can simulate the immunotherapy for cancer. These features are all present in the code and people can choose to turn them on and off at compiling time.
The book presents the basic model as well as the various customizations to implement the description of different diseases and the way they have been used in practice to produce new knowledge either from hypothesis or from lab-experiment data. In this respect, the book can be used as a practical guide to implement a computational model with which to study a specific disease and to try to address realistic clinical questions.
This concise and clearly written book will make your PubMed searches more productive.
This completely revised second edition of Brian Katcher's MEDLINE: a guide to effective searching in PubMed and other interfaces promotes the cultivation of an informed and thoughtful approach to searching in PubMed/MEDLINE and other interfaces to MEDLINE.
MEDLINE, the National Library of Medicine's on-line bibliographic database, is the premiere index to the world's biomedical literature. It is the primary component of PubMed. MEDLINE is exquisitely organized: each journal article is manually indexed under an average of a dozen Medical Subject Headings (MeSH Terms), one or more publication types, and more. An understanding of this organization is essential to effective searching. Any health professional, health sciences student, or researcher will benefit from reading this book. It explains the basics of formulating searches, shows how to put the main indexing elements in MEDLINE to best use, illustrates the importance of Medical Subject Headings (MeSH), provides guidance for framing questions, and backs everything up with practical examples.
MEDLINE: a guide to effective searching in PubMed and other interfaces is an essential resource for those concerned with evidence-based medicine and those engaged in biomedical research. Medical librarians and teachers of medical informatics will find this book to be useful in promoting the careful use of PubMed/MEDLINE.
This exciting new arena applies mathematical modeling and engineering methods to the study of biological systems. This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches. The work covers new concepts, methods for information storage, mining and knowledge extraction, reverse engineering of gene and metabolic networks, as well as modelling and simulation of multi-cellular systems. Central themes include strategies for predicting biological properties and methods for elucidating structure-function relationships.