Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Kernel Methods for Omics Data Mining: Theory and Applications

Kernel Methods for Omics Data Mining: Theory and Applications

Jiang, Hao
Ching, Wai-Ki

Hardcover

Series: Intelligent Control and Learning Systems, Book 10

Technology & EngineeringGeneral ComputersGeneral Mathematics

Currently unavailable to order

ISBN10: 9819531284
ISBN13: 9789819531288
Publisher: Springer
Published: Jan 13 2026
Pages: 232
Weight: 1.25
Height: 0.71 Width: 6.41 Depth: 9.38
Language: English

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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