Introduction to Mathematical Oncology (ePub)
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Extensively classroom-tested in undergraduate and graduate courses, this self-contained book 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.
John D. Nagy is a professor of biology and former chair of the Department of Life Sciences at Scottsdale Community College (SCC). He is also an adjunct professor in the School of Mathematical and Statistical Sciences at ASU. He is the founding director of an undergraduate research program in mathematical biology at both ASU and SCC. Dr. Nagy's primary research interests focus on the evolutionary dynamics of disease, including the application of mathematics and principles of evolutionary ecology to cancer and disease biology. He pioneered the "hypertumor" hypothesis and recently addressed how evolution shapes malignant characteristics of cancer. He earned a Ph.D. in mathematical biology from ASU.
Steffen E. Eikenberry is completing his M.D. at the University of Southern California (USC), as the final component of a combined M.D./Ph.D. program. He earned a Ph.D. in biomedical engineering from USC, with his dissertation studies focused on hierarchical model building for immune-pathogen interaction. Dr. Eikenberry is particularly interested in a careful approach to mathematical model building, understanding how specific functional forms affect model dynamics, and
- Autoren: Yang Kuang , John D. Nagy , Steffen E. Eikenberry
- 2018, 490 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1498752977
- ISBN-13: 9781498752978
- Erscheinungsdatum: 03.09.2018
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: ePub
- Größe: 13 MB
- Mit Kopierschutz
- Vorlesefunktion
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