Computational Life Sciences: Data Engineering and Data Mining for Life Sciences: Studies in Big Data, cartea 112
Editat de Jens Dörpinghaus, Vera Weil, Sebastian Schaaf, Alexander Apkeen Limba Engleză Hardback – 5 mar 2023
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Specificații
ISBN-13: 9783031084102
ISBN-10: 3031084101
Pagini: 598
Ilustrații: XII, 598 p. 259 illus., 155 illus. in color.
Dimensiuni: 155 x 235 x 35 mm
Greutate: 1.13 kg
Ediția:2022
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Big Data
Locul publicării:Cham, Switzerland
ISBN-10: 3031084101
Pagini: 598
Ilustrații: XII, 598 p. 259 illus., 155 illus. in color.
Dimensiuni: 155 x 235 x 35 mm
Greutate: 1.13 kg
Ediția:2022
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Big Data
Locul publicării:Cham, Switzerland
Cuprins
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.
Textul de pe ultima copertă
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.
Caracteristici
Introduces data engineering, data mining and other computational challenges in Life Science Informatics Presents quick introductions to all important topics like programming, databases, and data processing Offers helpful hints for further development