TY - GEN
T1 - Impacts of the different spline orders on the B-spline association estimator
AU - Kurt, Zeyneb
AU - Aydin, Nizamettin
AU - Altay, Gökmen
PY - 2013
Y1 - 2013
N2 - Gene Network Inference (GNI) algorithms enable searching the interactions among the several cell molecules. Many application fields such as computational biology and pharmacology utilize the GNI algorithms to illustrate the interaction networks of the cell molecules. Association score estimation is the most crucial step of the GNI applications. B-spline is a popular approach, which efficiently estimates the interaction scores between the variable (gene) pairs. In this study inference performance of the B-spline estimator according to the selected spline order is examined. In addition to evaluating B-spline performance according to the spline order, influences of using a frequently used pre-processing operation Copula Transform on the performance of B-spline is also examined. Conservative Causal Core network (C3NET) GNI algorithm is used in the experiments. At the overall analysis, B-spline estimator with the spline order 2 gave the best inference performance among the selected spline orders from 1 to 10.
AB - Gene Network Inference (GNI) algorithms enable searching the interactions among the several cell molecules. Many application fields such as computational biology and pharmacology utilize the GNI algorithms to illustrate the interaction networks of the cell molecules. Association score estimation is the most crucial step of the GNI applications. B-spline is a popular approach, which efficiently estimates the interaction scores between the variable (gene) pairs. In this study inference performance of the B-spline estimator according to the selected spline order is examined. In addition to evaluating B-spline performance according to the spline order, influences of using a frequently used pre-processing operation Copula Transform on the performance of B-spline is also examined. Conservative Causal Core network (C3NET) GNI algorithm is used in the experiments. At the overall analysis, B-spline estimator with the spline order 2 gave the best inference performance among the selected spline orders from 1 to 10.
UR - http://www.scopus.com/inward/record.url?scp=84894210958&partnerID=8YFLogxK
U2 - 10.1109/BIBE.2013.6701663
DO - 10.1109/BIBE.2013.6701663
M3 - Conference contribution
AN - SCOPUS:84894210958
SN - 9781479931637
T3 - 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
BT - 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
T2 - 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
Y2 - 10 November 2013 through 13 November 2013
ER -