Description

Book Synopsis

Omics Data: Acquisition and Mining.- Omics Data: Acquisition and Mining.-  Kernels and Spectrum Perturbations .-  Hadamard Kernel SVM with Applications.-  Regularized Multiple Kernel Learning Framework.-  Correlation Kernels for SVM Classification.- Weighted GTS Kernel and Applications in Drug Side-effect Profiles Prediction.- Single Cell RNA-sequencing Data Analysis.- Kernel Non-negative Matrix Factorization Framework for Single Cell Clustering.- Deep Neural Network with Kernel Nonnegative Matrix
Factorization for Single Cell Clustering.-  Multi-omics Single-cell Data Integration via High-order Kernel
Spectral Clustering.

Kernel Methods for Omics Data Mining

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    A Hardback by Hao Jiang

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      View other formats and editions of Kernel Methods for Omics Data Mining by Hao Jiang

      Publisher: Springer
      Publication Date: 13/12/2025
      ISBN13: 9789819531288, 978-9819531288
      ISBN10:
      Also in:
      Mathematics Optimization

      Description

      Book Synopsis

      Omics Data: Acquisition and Mining.- Omics Data: Acquisition and Mining.-  Kernels and Spectrum Perturbations .-  Hadamard Kernel SVM with Applications.-  Regularized Multiple Kernel Learning Framework.-  Correlation Kernels for SVM Classification.- Weighted GTS Kernel and Applications in Drug Side-effect Profiles Prediction.- Single Cell RNA-sequencing Data Analysis.- Kernel Non-negative Matrix Factorization Framework for Single Cell Clustering.- Deep Neural Network with Kernel Nonnegative Matrix
      Factorization for Single Cell Clustering.-  Multi-omics Single-cell Data Integration via High-order Kernel
      Spectral Clustering.

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