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New & Forthcoming Titles | Lecture Notes on Mathematical Modelling in the Life Sciences

Lecture Notes on Mathematical Modelling in the Life Sciences

Lecture Notes on Mathematical Modelling in the Life Sciences

Editors-in-chief: Stevens, Angela, Mackey, Michael
Series Editors: Burger, M., Chacron, M., Diekmann, O., Layton, A., Lei, J., Lewis, M., Mahadevan, L., Maini, P., Mimura, M., Neuhauser, C., Othmer, H.G., Peletier, M., Perelson, A.S., Peskin, C.S., Preziosi, L., Rubin, J., Santillan, M., Schütte, C., Sneyd, J., Swain, P., Tyran-Kamińska, M., Wu, J.

ISSN: 2193-4789

The rapid pace and development of the research in mathematics, biology and medicine has opened a niche for a new type of publication - short, up-to-date, readable lecture notes covering the breadth of mathematical modelling, analysis and computation in the life-sciences, at a high level, in both printed and electronic versions.

The volumes in this series are written in a style accessible to researchers, professionals and graduate students in the mathematical and biological sciences. They can serve as an introduction to recent and emerging subject areas and/or as an advanced teaching aid at colleges, institutes and universities. Besides monographs, we envision that this series will also provide an outlet for material less formally presented and more anticipatory of future needs, yet of immediate interest because of the novelty of its treatment of an application, or of the mathematics being developed in the context of exciting applications. It is important to note that the LMML focuses on books by one or more authors, not on edited volumes.

The topics in LMML range from the molecular through the organismal to the population level, e.g. genes and proteins, evolution, cell biology, developmental biology, neuroscience, organ, tissue and whole body science, immunology and disease, bioengineering and biofluids, population biology and systems biology. Mathematical methods include dynamical systems, ergodic theory, partial differential equations, calculus of variations, numerical analysis and scientific computing, differential geometry, topology, optimal control, probability, stochastics, statistical mechanics, combinatorics, algebra, number theory, etc., which contribute to a deeper understanding of biomedical problems.

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