Multiple-kernel learning for genomic data mining and prediction

Multiple-kernel learning for genomic data mining and prediction

Abstract Background Advances in medical technology have allowed for customized prognosis, diagnosis, and treatment regimens that utilize multiple heterogeneous data sources. Multiple kernel learning (MKL) is well suited for the integration of multiple high throughput data sources. MKL remains to be...

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Bibliographic Details
Main Authors: Christopher M. Wilson, Kaiqiao Li, Xiaoqing Yu, Pei-Fen Kuan, Xuefeng Wang
Format: Article
Language:English
Published: BMC 2019-08-01
Series:BMC Bioinformatics
Subjects:
Classification
Multiple kernel learning
Genomics
Data integration
Machine learning
Kernel methods
Online Access:http://link.springer.com/article/10.1186/s12859-019-2992-1

Internet

http://link.springer.com/article/10.1186/s12859-019-2992-1

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