TY  - BOOK
AU  - Vidyasagar,Mathukumalli
ED  - SpringerLink (Online service)
TI  - Computational Cancer Biology: An Interaction Network Approach 
T2  - SpringerBriefs in Electrical and Computer Engineering,
SN  - 9781447147510
AV  - QH324.2-324.25 
U1  - 570.285 23
PY  - 2012///
CY  - London
PB  - Springer London, Imprint: Springer
KW  - Computer science
KW  - Oncology
KW  - Bioinformatics
KW  - Biological models
KW  - Physiology
KW  - Mathematics
KW  - Statistics
KW  - Computer Science
KW  - Computational Biology/Bioinformatics
KW  - Physiological, Cellular and Medical Topics
KW  - Control
KW  - Statistics for Life Sciences, Medicine, Health Sciences
KW  - Systems Biology
KW  - Cancer Research
N1  - Introduction -- Inferring Genetic Regulatory Networks -- Context-specific Genomic Networks -- Analyzing Statistical Significance -- Separating Drivers from Passengers -- Some Research Directions
N2  - 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
UR  - http://dx.doi.org/10.1007/978-1-4471-4751-0
ER  -