Multiple-kernel learning for genomic data mining and prediction

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 under-utilized by ge...

詳細記述

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書誌詳細
主要な著者: Christopher M. Wilson, Kaiqiao Li, Xiaoqing Yu, Pei Fen Kuan, Xuefeng Wang
フォーマット: Artigo
言語:英語
出版事項: 2019
オンライン・アクセス:https://doi.org/10.1186/s12859-019-2992-1
https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-019-2992-1
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