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Bioinformatics Advance Access originally published online on January 29, 2004
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Bioinformatics 20(6) © Oxford University Press 2004; all rights reserved.

Modeling the relationship between LVAD support time and gene expression changes in the human heart by penalized partial least squares

Xiaohong Huang 1, Wei Pan 1,*, Soon Park 2, Xinqiang Han 3, Leslie W. Miller 3 and Jennifer Hall 3

1 Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA, 2 Cardiothoracic Surgery, Fairview Medical Center, University of Minnesota, Minneapolis, MN 55455, USA and 3 Department of Medicine, Cardiovascular Division, Medical School, University of Minnesota, Minneapolis, MN 55455, USA

Received on April 4, 2003 ; revised on October 28, 2003 ; accepted on October 30, 2003
Advance Access Publication January 29, 2004

Motivation: Heart failure affects more than 20 million people in the world. Heart transplantation is the most effective therapy, but the number of eligible patients far outweighs the number of available donor hearts. The left mechanical ventricular assist device (LVAD) has been developed as a successful substitution therapy that aids the failing ventricle while a patient is waiting for the donor heart. We obtained genomics data from paired human heart samples harvested at the time of LVAD implant and explant. The heart failure patients in our study were supported by the LVAD for various periods of time. The goal of this study is to model the relationship between the time of LVAD support and gene expression changes.

Results: To serve the purpose, we propose a novel penalized partial least squares (PPLS) method to build a regression model. Compared with partial least squares and Breiman's random forest method, PPLS gives the best prediction results for the LVAD data.

Contact: weip{at}biostat.umn.edu

* To whom correspondence should be addressed.


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