Title :
Machine learning for multimodality genomic signal processing
Author :
Kung, Sun-Yuan ; Mak, Man-Wai
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
fDate :
5/1/2006 12:00:00 AM
Abstract :
This paper discusses how machine learning can be applied to genomic signal processing, particularly via fusion of multiple biological or algorithmic modalities, to improve prediction performance.
Keywords :
biological techniques; genetic engineering; genetics; learning (artificial intelligence); medical signal processing; algorithmic modality fusion; machine learning; multimodality genomic signal processing; multiple biological fusion; prediction performance improvement; Bioinformatics; Biomedical signal processing; Cancer; Computational biology; Diversity reception; Feature extraction; Gene expression; Genomics; Machine learning; Signal processing;
Journal_Title :
Signal Processing Magazine, IEEE
DOI :
10.1109/MSP.2006.1628886
