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- Autorius: Hao Jiang, Wai-Ki Ching
- Leidėjas: Springer
- Metai: 2026
- Puslapiai: 244
- ISBN-10: 9819531284
- ISBN-13: 9789819531288
- Formatas: 16 x 24.1 x 1.8 cm, kieti viršeliai
- Kalba: Anglų
- Extra -15 % nuolaida šiai knygai su kodu: ENG15
Kernel Methods for Omics Data Mining (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
This book provides a new perspective on omics data modelling and analysis in bioinformatics area. Taking into consideration on the high-dimensionality and nonlinearity properties in omics data, the book detangles nonlinearity of data through novel perspectives of matrix optimization. Through integration of machine learning frameworks, various novel techniques are proposed to deal with the complexity of omics data analysis. Intuitive examples and illustrations are provided to help readers for understanding the key idea and general procedures in omics data analysis. This book is intended for academic scholars and practitioners who are interested in learning, computational biology, optimization and related fields. The graduate students in the above field can also benefit from this book.
EXTRA 15 % nuolaida su kodu: ENG15
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- Autorius: Hao Jiang, Wai-Ki Ching
- Leidėjas: Springer
- Metai: 2026
- Puslapiai: 244
- ISBN-10: 9819531284
- ISBN-13: 9789819531288
- Formatas: 16 x 24.1 x 1.8 cm, kieti viršeliai
- Kalba: Anglų
This book provides a new perspective on omics data modelling and analysis in bioinformatics area. Taking into consideration on the high-dimensionality and nonlinearity properties in omics data, the book detangles nonlinearity of data through novel perspectives of matrix optimization. Through integration of machine learning frameworks, various novel techniques are proposed to deal with the complexity of omics data analysis. Intuitive examples and illustrations are provided to help readers for understanding the key idea and general procedures in omics data analysis. This book is intended for academic scholars and practitioners who are interested in learning, computational biology, optimization and related fields. The graduate students in the above field can also benefit from this book.
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