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Computational life sciencesdata engineering and data mining for life sciences /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational life sciencesedited by Jens Dorpinghaus ... [et al.].
Reminder of title:	data engineering and data mining for life sciences /
other author:	Dorpinghaus, Jens.
Published:	Cham :Springer International Publishing :2022.
Description:	xii, 598 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Life sciencesData processing.
Online resource:	https://doi.org/10.1007/978-3-031-08411-9
ISBN:	9783031084119$q(electronic bk.)

Computational life sciencesdata 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.1..

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$q(electronic bk.)

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

619155
Life sciences
--Data processing.

LC Class. No.: QH324.2

Dewey Class. No.: 570.285574

Computational life sciencesdata engineering and data mining for life sciences /
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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.
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