Targeted Cancer Treatment in Silico
Small Molecule Inhibitors and Oncolytic Viruses
Nonfiction, Health & Well Being, Medical, Specialties, Oncology, Science & Nature, Mathematics, Applied
| Author: | Natalia L. Komarova, Dominik Wodarz | ISBN: | 9781461483014 |
| Publisher: | Springer New York | Publication: | November 19, 2013 |
| Imprint: | Birkhäuser | Language: | English |
| Author: | Natalia L. Komarova, Dominik Wodarz |
| ISBN: | 9781461483014 |
| Publisher: | Springer New York |
| Publication: | November 19, 2013 |
| Imprint: | Birkhäuser |
| Language: | English |
Countless medical researchers over the past century have been occupied by the search for a cure of cancer. So far, they have developed and implemented a wide range of treatment techniques, including surgery, chemo- and radiotherapy, antiangiogenic drugs, small molecule inhibitors, and oncolytic viruses. However, patterns of these treatments' effectiveness remain largely unclear, and a better understanding of how cancer therapies work has become a key research goal. Cancer Treatment in Silico provides the first in-depth study of approaching this understanding by modeling cancer treatments, both mathematically and through computer simulations.
The main goal of this book is to help expose students and researchers to in silico methods of studying cancer. It is intended for both the applied mathematics and experimental oncology communities, as mathematical models are playing an increasingly important role to supplement laboratory biology in the fight against cancer. Written at a level that generally requires little technical background, the work will be a valuable resource for scientists and students alike.
Countless medical researchers over the past century have been occupied by the search for a cure of cancer. So far, they have developed and implemented a wide range of treatment techniques, including surgery, chemo- and radiotherapy, antiangiogenic drugs, small molecule inhibitors, and oncolytic viruses. However, patterns of these treatments' effectiveness remain largely unclear, and a better understanding of how cancer therapies work has become a key research goal. Cancer Treatment in Silico provides the first in-depth study of approaching this understanding by modeling cancer treatments, both mathematically and through computer simulations.
The main goal of this book is to help expose students and researchers to in silico methods of studying cancer. It is intended for both the applied mathematics and experimental oncology communities, as mathematical models are playing an increasingly important role to supplement laboratory biology in the fight against cancer. Written at a level that generally requires little technical background, the work will be a valuable resource for scientists and students alike.
