東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Life sciences- Data processing." ]

切換: 標籤 | MARC模式 | ISBD

Computational life sciences = data e...

Dorpinghaus, Jens.

FindBook

Google Book

Amazon

博客來

Computational life sciences = data engineering and data mining for life sciences /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational life sciences/ edited by Jens Dorpinghaus ... [et al.].
其他題名:	data engineering and data mining for life sciences /
其他作者:	Dorpinghaus, Jens.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xii, 598 p. :ill., digital ;24 cm.
內容註:	Interesting 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.
Contained By:	Springer Nature eBook
標題:	Life sciences - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-031-08411-9
ISBN:	9783031084119

Computational life sciences = data engineering and data mining for life sciences /
Computational life sciencesdata engineering and data mining for life sciences /[electronic resource] :edited by Jens Dorpinghaus ... [et al.]. - Cham :Springer International Publishing :2022. - xii, 598 p. :ill., digital ;24 cm. - Studies in big data,v. 1122197-6511 ;. - Studies in big data ;v. 112..

Interesting 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.

This 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.

ISBN: 9783031084119

Standard No.: 10.1007/978-3-031-08411-9doiSubjects--Topical Terms:

2003176
Life sciences
--Data processing.

LC Class. No.: QH324.2

Dewey Class. No.: 570.285574

Computational life sciences = data engineering and data mining for life sciences /
LDR:02317nmm a2200337 a 4500 001 2308172
003 DE-He213
005 20230304090139.0
006 m d
007 cr nn 008maaau
008 230526s2022 sz s 0 eng d
020 $a 9783031084119 $q (electronic bk.)
020 $a 9783031084102 $q (paper)
024 7 $a 10.1007/978-3-031-08411-9 $2 doi
035 $a 978-3-031-08411-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QH324.2
072 7 $a UN $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 570.285574 $2 23
090 $a QH324.2 $b .C738 2022
245 0 0 $a Computational life sciences $h [electronic resource] : $b data engineering and data mining for life sciences / $c edited by Jens Dorpinghaus ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xii, 598 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6511 ; $v v. 112
505 0 $a Interesting 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.
520 $a This 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.
650 0 $a Life sciences $x Data processing. $3 2003176
650 0 $a Database management. $3 527442
650 0 $a Data mining. $3 562972
650 1 4 $a Data Engineering. $3 3409361
650 2 4 $a Bioinformatics. $3 553671
650 2 4 $a Big Data. $3 3134868
650 2 4 $a Computational Intelligence. $3 1001631
700 1 $a Dorpinghaus, Jens. $3 3614153
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in big data ; $v v. 112. $3 3614154
856 4 0 $u https://doi.org/10.1007/978-3-031-08411-9
950 $a Mathematics and Statistics (SpringerNature-11649)