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.
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 failurepatients 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.
Authors: Perrine Soret; Marta Avalos; Linda Wittkop; Daniel Commenges; Rodolphe Thiébaut Journal: BMC Med Res Methodol Date: 2018-12-04 Impact factor: 4.615
Authors: Claes Gustafsson; Jeremy Minshull; Sridhar Govindarajan; Jon Ness; Alan Villalobos; Mark Welch Journal: Protein Expr Purif Date: 2012-03-08 Impact factor: 1.650
Authors: Genevera I Allen; Christine Peterson; Marina Vannucci; Mirjana Maletić-Savatić Journal: Stat Anal Data Min Date: 2013-08-01 Impact factor: 1.051
Authors: Anita Hryniewicz-Jankowska; Pankaj K Choudhary; Larry P Ammann; Charles T Quinn; Steven R Goodman Journal: Exp Biol Med (Maywood) Date: 2008-12-08