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010   $a3-031-08411-X
024 7 $a10.1007/978-3-031-08411-9
035   $a(MiAaPQ)EBC7209553
035   $a(Au-PeEL)EBL7209553
035   $a(CKB)26240842300041
035   $a(DE-He213)978-3-031-08411-9
035   $a(PPN)26909539X
035   $a(EXLCZ)9926240842300041
100   $a20230526d2023      uy             0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aComputational life sciences $edata engineering and data mining for life sciences /$fedited by Jens Do?rpinghaus [and three others]
205   $a1st ed. 2022.
210  1$aCham, Switzerland :$cSpringer,$d[2023]
210  4$d©2023
215   $a1 online resource (593 pages)
225 1 $aStudies in Big Data,$x2197-6511 ;$v112
300   $aIncludes index.
311 08$aPrint version: Dörpinghaus, Jens Computational Life Sciences Cham : Springer International Publishing AG,c2023 9783031084102 
327   $aInteresting Programming Languages used in Life Sciences -- Introduction to Java -- Basic Data Processing -- Algorithm Design -- Data and Knowledge Management -- Databases and Knowledge Graphs -- Knowledge Discovery and AI approaches for the Life Sciences -- Longitudinal Data.
330   $aThis book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise. .
410  0$aStudies in Big Data,$x2197-6511 ;$v112
606   $aBig data
606   $aCiències de la vida$2thub
606   $aProcessament de dades$2thub
606   $aGestió de bases de dades$2thub
606   $aMineria de dades$2thub
608   $aLlibres electrònics$2thub
615  0$aBig data.
615  7$aCiències de la vida
615  7$aProcessament de dades
615  7$aGestió de bases de dades
615  7$aMineria de dades
676   $a005.7
702   $aDo?rpinghaus$b Jens
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910678263603321
996   $aComputational Life Sciences$93067822
997   $aUNINA