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Computational cancer biology : an interaction network approach

Autore: M Vidyasagar
Editore: London ; New York : Springer, ©2012.
Serie: SpringerBriefs in electrical and computer engineering., Control, automation and robotics.
Edizione/Formato:   eBook : Document : EnglishVedi tutte le edizioni e i formati
Banca dati:WorldCat
Sommario:
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  Per saperne di più…
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Dettagli

Genere/forma: Electronic books
Tipo materiale: Document, Risorsa internet
Tipo documento: Internet Resource, Computer File
Tutti gli autori / Collaboratori: M Vidyasagar
ISBN: 9781447147510 1447147510
Numero OCLC: 822978249
Descrizione: 1 online resource (xii, 80 p.) : ill.
Contenuti: The Role of System Theory in Biology --
Analyzing Statistical Significance --
Inferring Gene Interaction Networks --
Some Research Directions.
Titolo della serie: SpringerBriefs in electrical and computer engineering., Control, automation and robotics.
Responsabilità: Mathukumalli Vidyasagar.
Maggiori informazioni:

Abstract:

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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