Targeted Cancer Treatment In Silico Small Molecule Inhibitors And Oncolytic Viruses

  • 1 Want to read
Locate

My Reading Lists:

Create a new list

Check-In

×Close
Add an optional check-in date. Check-in dates are used to track yearly reading goals.
Today

  • 1 Want to read

Buy this book

Last edited by MARC Bot
October 2, 2024 | History

Targeted Cancer Treatment In Silico Small Molecule Inhibitors And Oncolytic Viruses

  • 1 Want to read

This monograph provides the first in-depth study of how mathematical and computational approaches can be used to advance our understanding of cancer therapies and to improve treatment design and outcome. Over the past century, the search for a cancer cure has been a primary occupation of medical researchers. So far, it has led to a wide range of treatment techniques, including surgery, chemo- and radiotherapy, antiangiogenic drugs, and most recently, small molecule inhibitors and oncolytic viruses. Each treatment tends to have a certain effectiveness in a specific class of patients, but it is often unclear what exactly causes it to succeed or fail. Recent technological advances have given rise to an ever increasing pool of data and information that highlight the complexity underlying the cancers and their response to treatment. Next to experimental and clinical research, mathematical and computational approaches are becoming an indispensible tool to understand this complexity. Targeted Cancer Treatment in Silico is organized into two parts, corresponding to two types of targeted cancer treatment: small molecule inhibitors and oncolytic viruses. In each part, the authors provide a brief overview of the treatment’s biological basis and present the mathematical methods most suitable for modeling it. Additionally, they discuss how these methods can be applied to answer relevant questions about treatment mechanisms and propose modifications to treatment approaches that may potentially increase success rates. The book is intended for both the applied mathematics and experimental oncology communities, as mathematical models are becoming an increasingly important supplement to laboratory biology in the fight against cancer. Written at a level that generally requires little technical background, it will be a valuable resource for scientists and graduate students alike, and can also serve as an upper-division undergraduate or graduate textbook.

Publish Date
Pages
227

Buy this book

Book Details


Classifications

Library of Congress
QH323.5RC261-271QH32, RC270.8 .K67 2014, QH323.5

ID Numbers

Open Library
OL26051657M
ISBN 13
9781461483007
LCCN
2013945158

Community Reviews (0)

Feedback?
No community reviews have been submitted for this work.

Lists

This work does not appear on any lists.

History

Download catalog record: RDF / JSON
October 2, 2024 Edited by MARC Bot import existing book
November 12, 2020 Edited by MARC Bot import existing book
August 3, 2020 Edited by ImportBot import existing book
October 14, 2016 Edited by Mek Added new cover
October 14, 2016 Created by Mek Added new book.