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001 978-1-4471-4751-0
003 DE-He213
005 20140220083237.0
007 cr nn 008mamaa
008 121205s2012 xxk| s |||| 0|eng d
020 _a9781447147510
_9978-1-4471-4751-0
024 7 _a10.1007/978-1-4471-4751-0
_2doi
050 4 _aQH324.2-324.25
072 7 _aPSA
_2bicssc
072 7 _aUB
_2bicssc
072 7 _aCOM014000
_2bisacsh
082 0 4 _a570.285
_223
100 1 _aVidyasagar, Mathukumalli.
_eauthor.
245 1 0 _aComputational Cancer Biology
_h[electronic resource] :
_bAn Interaction Network Approach /
_cby Mathukumalli Vidyasagar.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2012.
300 _aXII, 80 p. 11 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
505 0 _aIntroduction -- Inferring Genetic Regulatory Networks -- Context-specific Genomic Networks -- Analyzing Statistical Significance -- Separating Drivers from Passengers -- Some Research Directions.
520 _aThis 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.
650 0 _aComputer science.
650 0 _aOncology.
650 0 _aBioinformatics.
650 0 _aBiological models.
650 0 _aPhysiology
_xMathematics.
650 0 _aStatistics.
650 1 4 _aComputer Science.
650 2 4 _aComputational Biology/Bioinformatics.
650 2 4 _aPhysiological, Cellular and Medical Topics.
650 2 4 _aControl.
650 2 4 _aStatistics for Life Sciences, Medicine, Health Sciences.
650 2 4 _aSystems Biology.
650 2 4 _aCancer Research.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781447147503
830 0 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-4751-0
912 _aZDB-2-SCS
999 _c100792
_d100792