TY - GEN
T1 - Gene expression profiling and machine learning to understand and predict primary graft dysfunction
AU - Ray, Monika
AU - Dharmarajan, Sekhar
AU - Freudenberg, Johannes
AU - Patterson, G. Alexander
AU - Zhang, Weixiong
PY - 2007
Y1 - 2007
N2 - Lung transplantation is the treatment of choice for end-stage pulmonary diseases. A limited donor supply has resulted in 4000 patients on the waiting list. Currently, 10-20% of donor organs are deemed suitable under the selection criteria, of which 15-25% fails due to primary graft dysfunction (PGD). In this study, we attempt to further our understanding of PGD by observing the changes in gene expression across donor lungs that developed PGD versus those that did not. Our second goal is to use a machine learning tool - support vector machine (SVM), to distinguish unsuitable donor lungs from suitable donor lungs, based on the gene expression data. Classification results for distinguishing suitable and unsuitable lungs for transplantation using a SVM were promising. This is the first such attempt to use human lungs used for transplantation and combine the identification of a molecular signature for PGD, with machine learning methods for donor lung prediction.
AB - Lung transplantation is the treatment of choice for end-stage pulmonary diseases. A limited donor supply has resulted in 4000 patients on the waiting list. Currently, 10-20% of donor organs are deemed suitable under the selection criteria, of which 15-25% fails due to primary graft dysfunction (PGD). In this study, we attempt to further our understanding of PGD by observing the changes in gene expression across donor lungs that developed PGD versus those that did not. Our second goal is to use a machine learning tool - support vector machine (SVM), to distinguish unsuitable donor lungs from suitable donor lungs, based on the gene expression data. Classification results for distinguishing suitable and unsuitable lungs for transplantation using a SVM were promising. This is the first such attempt to use human lungs used for transplantation and combine the identification of a molecular signature for PGD, with machine learning methods for donor lung prediction.
KW - Donor lungs evaluation
KW - Gene network analysis
KW - Lung transplantation
KW - Primary graft dysfunction
KW - SVM classification
UR - http://www.scopus.com/inward/record.url?scp=47649095727&partnerID=8YFLogxK
U2 - 10.1109/BIBE.2007.4375692
DO - 10.1109/BIBE.2007.4375692
M3 - Conference contribution
AN - SCOPUS:47649095727
SN - 1424415098
SN - 9781424415090
T3 - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
SP - 1076
EP - 1080
BT - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
T2 - 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Y2 - 14 January 2007 through 17 January 2007
ER -