000 03380nam a22005175i 4500
001 978-1-4939-1381-7
003 DE-He213
005 20200421112228.0
007 cr nn 008mamaa
008 140830s2014 xxu| s |||| 0|eng d
020 _a9781493913817
_9978-1-4939-1381-7
024 7 _a10.1007/978-1-4939-1381-7
_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 _aXu, Ying.
_eauthor.
245 1 0 _aCancer Bioinformatics
_h[electronic resource] /
_cby Ying Xu, Juan Cui, David Puett.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aXXVI, 368 p. 68 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aBasic cancer biology -- Omic data, information derivable and computational needs -- Cancer classification and molecular signature identification -- Understanding cancer at the genomic level -- Elucidation of cancer divers through comparative omic analyses -- Hyaluronic acid: A key facilitator of cancer evolution -- Multiple routes for survival: Understanding how cancer evades apoptosis -- Cancer development in competitive and hostile environments -- Cell proliferation from regulated to deregulated state via epigenomic responses -- Understanding cancer invasion and metastasis -- Cancer after metastasis: The second transformation -- Searching for cancer biomarkers in human body fluids -- In silico investigation of cancer using publicly available data -- Understanding cancer as an evolving complex system: our perspective.
520 _aThis book provides a framework for computational researchers studying the basics of cancer through comparative analyses of omic data. It discusses how key cancer pathways can be analyzed and discovered to derive new insights into the disease and identifies diagnostic and prognostic markers for cancer. Chapters explain the basic cancer biology and how cancer develops, including the many potential survival routes. The examination of gene-expression patterns uncovers commonalities across multiple cancers and specific characteristics of individual cancer types. The authors also treat cancer as an evolving complex system, explore future case studies, and summarize the essential online data sources. Cancer Bioinformatics is designed for practitioners and researchers working in cancer research and bioinformatics. It is also suitable as a secondary textbook for advanced-level students studying computer science, biostatistics or biomedicine.
650 0 _aComputer science.
650 0 _aCancer research.
650 0 _aBioinformatics.
650 0 _aSystems biology.
650 1 4 _aComputer Science.
650 2 4 _aComputational Biology/Bioinformatics.
650 2 4 _aCancer Research.
650 2 4 _aSystems Biology.
650 2 4 _aBiomedicine general.
700 1 _aCui, Juan.
_eauthor.
700 1 _aPuett, David.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781493913800
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-1381-7
912 _aZDB-2-SCS
942 _cEBK
999 _c57801
_d57801