Computational Cancer Biology

An Interaction Network Approach

  • Mathukumalli Vidyasagar

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Also part of the SpringerBriefs in Control, Automation and Robotics book sub series (BRIEFSCONTROL)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Mathukumalli Vidyasagar
    Pages 1-12
  3. Mathukumalli Vidyasagar
    Pages 13-29
  4. Mathukumalli Vidyasagar
    Pages 31-68
  5. Mathukumalli Vidyasagar
    Pages 69-80

About this book


This brief introduces readers to various problems in cancer biology that are amenable to analysis using methods of probability theory and statistics, building on only a basic background in these two topics.


Aside from providing a self-contained introduction to several aspects of basic biology and to cancer, as well as to the techniques from statistics most commonly used in cancer biology, the brief describes several methods for inferring gene interaction networks from expression data, including one that is reported for the first time in the brief.  The application of these methods is illustrated on actual data from cancer cell lines.  Some promising directions for new research are also discussed.


After reading the brief, engineers and mathematicians should be able to collaborate fruitfully with their biologist colleagues on a wide variety of problems.


Biologically-derived Control Systems Cancer Biology Computational Biology Graph Theory Information Theory Markov Processes

Authors and affiliations

  • Mathukumalli Vidyasagar
    • 1
  1. 1., Bioengineering DepartmentThe University of Texas at DallasRichardsonUSA

Bibliographic information