Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
There exists a large and growing number of proposed estimation methods but little conclusive evidence ranking one method over another. Prior effort estimation studies suffered fro...
Tim Menzies, Omid Jalali, Jairus Hihn, Daniel Bake...
— The genetic causes of many monogenic diseases have already been discovered. However, most common diseases are actually the result of complex nonlinear interactions between mult...
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...