000 03921nam a22005895i 4500
001 978-3-319-03035-7
003 DE-He213
005 20140220082512.0
007 cr nn 008mamaa
008 131118s2014 gw | s |||| 0|eng d
020 _a9783319030357
_9978-3-319-03035-7
024 7 _a10.1007/978-3-319-03035-7
_2doi
050 4 _aQH324.2-324.25
072 7 _aPS
_2bicssc
072 7 _aUB
_2bicssc
072 7 _aSCI086000
_2bisacsh
072 7 _aCOM018000
_2bisacsh
082 0 4 _a570.285
_223
100 1 _aPlattner, Hasso.
_eeditor.
245 1 0 _aHigh-Performance In-Memory Genome Data Analysis
_h[electronic resource] :
_bHow In-Memory Database Technology Accelerates Personalized Medicine /
_cedited by Hasso Plattner, Matthieu-P. Schapranow.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXXI, 223 p. 78 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIn-Memory Data Management Research,
_x2196-8055
505 0 _a1. Innovations for Personalized Medicine -- 2. Modeling Genome Data Processing Pipelines -- 3. Scheduling and Execution of Genome Data processing Pipelines -- 4. Exchanging Medical Knowledge -- 5. Billing Processes in Personalized Medicine -- 6. Real-time Analysis of Patient Cohorts -- 7. Ad-hoc Analysis of Genetic Pathways -- 8. Combined Search in Structured and Unstructured Medical Data -- Real-time Collaboration in the Course of Personalized Medicine.
520 _a Recent achievements in hardware and software developments have enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of data, such as diagnoses, therapies, and human genome data. This book shares the latest research results of applying in-memory data management to personalized medicine, changing it from computational possibility to clinical reality. The authors provide details on innovative approaches to enabling the processing, combination, and analysis of relevant data in real-time. The book bridges the gap between medical experts, such as physicians, clinicians, and biological researchers, and technology experts, such as software developers, database specialists, and statisticians. Topics covered in this book include - amongst others - modeling of genome data processing and analysis pipelines, high-throughput data processing, exchange of sensitive data and protection of intellectual property. Beyond that, it shares insights on research prototypes for the analysis of patient cohorts, topology analysis of biological pathways, and combined search in structured and unstructured medical data, and outlines completely new processes that have now become possible due to interactive data analyses.
650 0 _aLife sciences.
650 0 _aMedical records
_xData processing.
650 0 _aBioinformatics.
650 0 _aBiology
_xData processing.
650 0 _aGenetics
_xMathematics.
650 0 _aMathematical statistics.
650 0 _aManagement information systems.
650 1 4 _aLife Sciences.
650 2 4 _aComputer Appl. in Life Sciences.
650 2 4 _aComputational Biology/Bioinformatics.
650 2 4 _aBusiness Information Systems.
650 2 4 _aStatistics and Computing/Statistics Programs.
650 2 4 _aGenetics and Population Dynamics.
650 2 4 _aHealth Informatics.
700 1 _aSchapranow, Matthieu-P.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319030340
830 0 _aIn-Memory Data Management Research,
_x2196-8055
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-03035-7
912 _aZDB-2-SBE
999 _c92952
_d92952