Muutke küpsiste eelistusi

Computational Life Sciences: Data Engineering and Data Mining for Life Sciences 2022 ed. [Pehme köide]

Edited by , Edited by , Edited by , Edited by
  • Formaat: Paperback / softback, 598 pages, kõrgus x laius: 235x155 mm, 155 Illustrations, color; 104 Illustrations, black and white; XII, 598 p. 259 illus., 155 illus. in color., 1 Paperback / softback
  • Sari: Studies in Big Data 112
  • Ilmumisaeg: 05-Mar-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031084136
  • ISBN-13: 9783031084133
Teised raamatud teemal:
  • Pehme köide
  • Hind: 159,88 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 188,09 €
  • Säästad 15%
  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
  • Formaat: Paperback / softback, 598 pages, kõrgus x laius: 235x155 mm, 155 Illustrations, color; 104 Illustrations, black and white; XII, 598 p. 259 illus., 155 illus. in color., 1 Paperback / softback
  • Sari: Studies in Big Data 112
  • Ilmumisaeg: 05-Mar-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031084136
  • ISBN-13: 9783031084133
Teised raamatud teemal:
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.





 
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.