Computational life sciences : data engineering and data mining for life sciences
Author(s)
Bibliographic Information
Computational life sciences : data engineering and data mining for life sciences
（Studies in big data, 112）
Springer, c2022
Available at 1 libraries
Note
Other editors: Vera Weil, Sebastian Schaaf, Alexander Apke
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
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.
by "Nielsen BookData"