Introduction to Mathematical Oncology:
Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existi...
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| Beteiligte Personen: | , , |
|---|---|
| Körperschaft: | |
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
[Erscheinungsort nicht ermittelbar]
Chapman and Hall/CRC
2016
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| Ausgabe: | 1st edition. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781498785532/?ar |
| Zusammenfassung: | Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding, the text describes well-known, practical, and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure, such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models, including cell quota-based population growth models, with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical, biological, and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses, this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways, including a single-semester undergraduate course, a more ambitious graduate course, or a full-year sequence on mathematical oncology. |
| Beschreibung: | Online resource; Title from title page (viewed April 5, 2016) |
| Umfang: | 1 Online-Ressource (470 Seiten) |
| ISBN: | 9781498785532 |
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| spelling | Kuang, Yang VerfasserIn aut Introduction to Mathematical Oncology Kuang, Yang 1st edition. [Erscheinungsort nicht ermittelbar] Chapman and Hall/CRC 2016 1 Online-Ressource (470 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; Title from title page (viewed April 5, 2016) Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding, the text describes well-known, practical, and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure, such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models, including cell quota-based population growth models, with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical, biological, and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses, this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways, including a single-semester undergraduate course, a more ambitious graduate course, or a full-year sequence on mathematical oncology. Mathematics Science Mathématiques Sciences applied mathematics mathematics sciences (philosophy) science (modern discipline) Nagy, John VerfasserIn aut Eikenberry, Steffen VerfasserIn aut Safari, an O'Reilly Media Company. MitwirkendeR ctb |
| spellingShingle | Kuang, Yang Nagy, John Eikenberry, Steffen Introduction to Mathematical Oncology Mathematics Science Mathématiques Sciences applied mathematics mathematics sciences (philosophy) science (modern discipline) |
| title | Introduction to Mathematical Oncology |
| title_auth | Introduction to Mathematical Oncology |
| title_exact_search | Introduction to Mathematical Oncology |
| title_full | Introduction to Mathematical Oncology Kuang, Yang |
| title_fullStr | Introduction to Mathematical Oncology Kuang, Yang |
| title_full_unstemmed | Introduction to Mathematical Oncology Kuang, Yang |
| title_short | Introduction to Mathematical Oncology |
| title_sort | introduction to mathematical oncology |
| topic | Mathematics Science Mathématiques Sciences applied mathematics mathematics sciences (philosophy) science (modern discipline) |
| topic_facet | Mathematics Science Mathématiques Sciences applied mathematics mathematics sciences (philosophy) science (modern discipline) |
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