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Titolo: | Computational life sciences : data engineering and data mining for life sciences / / edited by Jens Dörpinghaus [and three others] |
Pubblicazione: | Cham, Switzerland : , : Springer, , [2023] |
©2023 | |
Edizione: | 1st ed. 2022. |
Descrizione fisica: | 1 online resource (593 pages) |
Disciplina: | 005.7 |
Soggetto topico: | Big data |
Ciències de la vida | |
Processament de dades | |
Gestió de bases de dades | |
Mineria de dades | |
Soggetto genere / forma: | Llibres electrònics |
Persona (resp. second.): | DörpinghausJens |
Note generali: | Includes index. |
Nota di contenuto: | 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. |
Sommario/riassunto: | 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. . |
Titolo autorizzato: | Computational Life Sciences |
ISBN: | 3-031-08411-X |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910678263603321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |