kernel methods omics data von jiang hao (6 Ergebnisse)

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Zustand: Brand New. 180 pages. 9.25x6.10x9.49 inches. In Stock.

Buch. Zustand: Neu. Kernel Methods for Omics Data Mining | Theory and Applications | Hao Jiang (u. a.) | Buch | Intelligent Control and Learning Systems | x | Englisch | 2026 | Springer | EAN 9789819531288 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Buch. Zustand: Neu. Neuware - 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.

Buch. Zustand: Neu. Neuware -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. 244 pp. Englisch.