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Machine learning for multimodality genomic signal processing

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2 Author(s)
Sun-Yuan Kung ; Dept. of Electr. Eng., Princeton Univ., NJ, USA ; Man-Wai Mak

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.

Published in:

IEEE Signal Processing Magazine  (Volume:23 ,  Issue: 3 )