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Computational cancer biology : an interaction network approach

著者: M Vidyasagar
出版商: London ; New York : Springer, ©2012.
丛书: SpringerBriefs in electrical and computer engineering., Control, automation and robotics.
版本/格式:   电子图书 : 文献 : 英语查看所有的版本和格式
数据库:WorldCat
提要:
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  再读一些...
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详细书目

类型/形式: Electronic books
附加的形体格式: Print version:
Vidyasagar, M. (Mathukumalli), 1947-
Computational cancer biology.
London ; New York : Springer, ©2012
(DLC) 2012950853
材料类型: 文献, 互联网资源
文件类型: 互联网资源, 计算机文档
所有的著者/提供者: M Vidyasagar
ISBN: 9781447147510 1447147510 1447147502 9781447147503
OCLC号码: 822978249
描述: 1 online resource (xii, 80 pages) : illustrations.
内容: The Role of System Theory in Biology --
Analyzing Statistical Significance --
Inferring Gene Interaction Networks --
Some Research Directions.
丛书名: SpringerBriefs in electrical and computer engineering., Control, automation and robotics.
责任: Mathukumalli Vidyasagar.

摘要:

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.
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