书目名称 | Mathematical, Computational and Experimental T Cell Immunology | 编辑 | Carmen Molina-París,Grant Lythe | 视频video | | 概述 | Features pedagogical content for readers with limited experience in T cell immunology and/or mathematical and computational modelling.Provides a comprehensive, cutting-edge overview of this multidisci | 图书封面 |  | 描述 | .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.. | 出版日期 | Book 2021 | 关键词 | cell biology; data-driven modeling; thymic selection; thymus; modeling; immune | 版次 | 1 | doi | https://doi.org/10.1007/978-3-030-57204-4 | isbn_softcover | 978-3-030-57206-8 | isbn_ebook | 978-3-030-57204-4 | copyright | Springer Nature Switzerland AG 2021 |
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