Mathematical, Computational and Experimental T Cell Immunology

Mathematical, Computational and Experimental T Cell Immunology PDF Author: Carmen Molina-París
Publisher: Springer Nature
ISBN: 3030572048
Category : Medical
Languages : en
Pages : 300

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Book Description
Mathematical, statistical, and computational methods enable multi-disciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. This volume collects a representative sample of studies in T cell immunology that illustrate the benefits of modelling-experimental collaborations and which have proven valuable or even ground-breaking. Studies include thymic selection, T cell repertoire diversity, T cell homeostasis in health and disease, T cell-mediated immune responses, T cell memory, T cell signalling and analysis of flow cytometry data sets. Contributing authors are leading scientists in the area of experimental, computational, and mathematical immunology. Each chapter includes state-of-the-art and pedagogical content, making this book accessible to readers with limited experience in T cell immunology and/or mathematical and computational modelling.

Mathematical, Computational and Experimental T Cell Immunology

Mathematical, Computational and Experimental T Cell Immunology PDF Author: Carmen Molina-París
Publisher: Springer Nature
ISBN: 3030572048
Category : Medical
Languages : en
Pages : 300

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Book Description
Mathematical, statistical, and computational methods enable multi-disciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. This volume collects a representative sample of studies in T cell immunology that illustrate the benefits of modelling-experimental collaborations and which have proven valuable or even ground-breaking. Studies include thymic selection, T cell repertoire diversity, T cell homeostasis in health and disease, T cell-mediated immune responses, T cell memory, T cell signalling and analysis of flow cytometry data sets. Contributing authors are leading scientists in the area of experimental, computational, and mathematical immunology. Each chapter includes state-of-the-art and pedagogical content, making this book accessible to readers with limited experience in T cell immunology and/or mathematical and computational modelling.

Killer Cell Dynamics

Killer Cell Dynamics PDF Author: Dominik Wodarz
Publisher: Springer Science & Business Media
ISBN: 0387687335
Category : Mathematics
Languages : en
Pages : 226

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Book Description
This book reviews how mathematical and computational approaches can be useful to help us understand how killer T-cell responses work to fight viral infections. It also demonstrates, in a writing style that exemplifies the point, that such mathematical and computational approaches are most valuable when coupled with experimental work through interdisciplinary collaborations. Designed to be useful to immunoligists and viroligists without extensive computational background, the book covers a broad variety of topics, including both basic immunological questions and the application of these insights to the understanding and treatment of pathogenic human diseases.

A Course in Mathematical Biology

A Course in Mathematical Biology PDF Author: Gerda de Vries
Publisher: SIAM
ISBN: 0898718252
Category : Mathematics
Languages : en
Pages : 307

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Book Description
This is the only book that teaches all aspects of modern mathematical modeling and that is specifically designed to introduce undergraduate students to problem solving in the context of biology. Included is an integrated package of theoretical modeling and analysis tools, computational modeling techniques, and parameter estimation and model validation methods, with a focus on integrating analytical and computational tools in the modeling of biological processes. Divided into three parts, it covers basic analytical modeling techniques; introduces computational tools used in the modeling of biological problems; and includes various problems from epidemiology, ecology, and physiology. All chapters include realistic biological examples, including many exercises related to biological questions. In addition, 25 open-ended research projects are provided, suitable for students. An accompanying Web site contains solutions and a tutorial for the implementation of the computational modeling techniques. Calculations can be done in modern computing languages such as Maple, Mathematica, and MATLAB?.

Computational Immunology

Computational Immunology PDF Author: Josep Bassaganya-Riera
Publisher: Academic Press
ISBN: 0128037156
Category : Medical
Languages : en
Pages : 212

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Book Description
Computational Immunology: Models and Tools encompasses 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 complexity - Provides a detailed view on cutting-edge tools for modeling that are useful to experimentalists with limited computational skills - Explores the usage of simulation for hypothesis generation, helping the reader to understand the most valuable points on experimental setting

Exploring Mathematical Modeling in Biology Through Case Studies and Experimental Activities

Exploring Mathematical Modeling in Biology Through Case Studies and Experimental Activities PDF Author: Rebecca Sanft
Publisher: Academic Press
ISBN: 0128195959
Category : Science
Languages : en
Pages : 260

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Book Description
Exploring Mathematical Modeling in Biology through Case Studies and Experimental Activities provides supporting materials for courses taken by students majoring in mathematics, computer science or in the life sciences. The book's cases and lab exercises focus on hypothesis testing and model development in the context of real data. The supporting mathematical, coding and biological background permit readers to explore a problem, understand assumptions, and the meaning of their results. The experiential components provide hands-on learning both in the lab and on the computer. As a beginning text in modeling, readers will learn to value the approach and apply competencies in other settings. Included case studies focus on building a model to solve a particular biological problem from concept and translation into a mathematical form, to validating the parameters, testing the quality of the model and finally interpreting the outcome in biological terms. The book also shows how particular mathematical approaches are adapted to a variety of problems at multiple biological scales. Finally, the labs bring the biological problems and the practical issues of collecting data to actually test the model and/or adapting the mathematics to the data that can be collected.

Computational Biology Of Cancer: Lecture Notes And Mathematical Modeling

Computational Biology Of Cancer: Lecture Notes And Mathematical Modeling PDF Author: Dominik Wodarz
Publisher: World Scientific
ISBN: 9814481874
Category : Science
Languages : en
Pages : 266

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Book Description
The book shows how mathematical and computational models can be used to study cancer biology. It introduces the concept of mathematical modeling and then applies it to a variety of topics in cancer biology. These include aspects of cancer initiation and progression, such as the somatic evolution of cells, genetic instability, and angiogenesis. The book also discusses the use of mathematical models for the analysis of therapeutic approaches such as chemotherapy, immunotherapy, and the use of oncolytic viruses.

Computational Immunology

Computational Immunology PDF Author: Shyamasree Ghosh
Publisher: CRC Press
ISBN: 1351023497
Category : Medical
Languages : en
Pages : 201

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Book Description
Computational Immunology: Applications focuses on different mathematical models, statistical tools, techniques, and computational modelling that helps in understanding complex phenomena of the immune system and its biological functions. The book also focuses on the latest developments in computational biology in designing of drugs, targets, biomarkers for early detection and prognosis of a disease. It highlights the applications of computational methods in deciphering the complex processes of the immune system and its role in health and disease. This book discusses the most essential topics, including Next generation sequencing (NGS) and computational immunology Computational modelling and biology of diseases Drug designing Computation and identification of biomarkers Application in organ transplantation Application in disease detection and therapy Computational methods and applications in understanding of the invertebrate immune system S Ghosh is MSc, PhD, PGDHE, PGDBI, is PhD from IICB, CSIR, Kolkata, awarded the prestigious National Scholarship from the Government of India. She has worked and published extensively in glycobiology, sialic acids, immunology, stem cells and nanotechnology. She has authored several publications that include books and encyclopedia chapters in reputed journals and books.

Computational Systems Biology of Cancer

Computational Systems Biology of Cancer PDF Author: Emmanuel Barillot
Publisher: CRC Press
ISBN: 1439831440
Category : Science
Languages : en
Pages : 463

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Book Description
The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.

Theoretical and Experimental Insights into Immunology

Theoretical and Experimental Insights into Immunology PDF Author: Alan S. Perelson
Publisher: Springer Science & Business Media
ISBN: 3642769772
Category : Medical
Languages : en
Pages : 485

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Book Description
Immunology is largely a science of observation and experimentation, and these approaches have lead to great increases in our knowledge of the genes, molecules and cells of the immune system. This book is an up-to-date discussion of the current state of modelling and theoretical work in immunology, of the impact of theory on experiment, and of future directions for theoretical research. Among the topics discussed are the function and evolution of the immune system, computer modelling of the humoral immune response and of idiotypic networks and idiotypic mimicry, T-cell memory, cryptic peptides, new views and models of AIDS and autoimmunity, and the shaping of the immune repertoire by early presented antigens and self immunoglobulin.

Systems Immunology

Systems Immunology PDF Author: Jayajit Das
Publisher: CRC Press
ISBN: 1498717411
Category : Science
Languages : en
Pages : 355

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Book Description
"Taken together, the body of information contained in this book provides readers with a bird’s-eye view of different aspects of exciting work at the convergence of disciplines that will ultimately lead to a future where we understand how immunity is regulated, and how we can harness this knowledge toward practical ends that reduce human suffering. I commend the editors for putting this volume together." –Arup K. Chakraborty, Robert T. Haslam Professor of Chemical Engineering, and Professor of Physics, Chemistry, and Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA New experimental techniques in immunology have produced large and complex data sets that require quantitative modeling for analysis. This book provides a complete overview of computational immunology, from basic concepts to mathematical modeling at the single molecule, cellular, organism, and population levels. It showcases modern mechanistic models and their use in making predictions, designing experiments, and elucidating underlying biochemical processes. It begins with an introduction to data analysis, approximations, and assumptions used in model building. Core chapters address models and methods for studying immune responses, with fundamental concepts clearly defined. Readers from immunology, quantitative biology, and applied physics will benefit from the following: Fundamental principles of computational immunology and modern quantitative methods for studying immune response at the single molecule, cellular, organism, and population levels. An overview of basic concepts in modeling and data analysis. Coverage of topics where mechanistic modeling has contributed substantially to current understanding. Discussion of genetic diversity of the immune system, cell signaling in the immune system, immune response at the cell population scale, and ecology of host-pathogen interactions.