Application of SPLINDID, a semiparametric, model-based method for pharmacogenomic modeling of mRNA dynamics.
OBJECTIVE
This study was conducted to evaluate the applicability of SPLINDID, a semiparametric, model-based approach for obtaining transcription rates from the pharmacodynamics of mRNA expression.


METHODS
A nonparametric exponential cubic spline function was used to obtain the transcription rate profile and the dynamics of mRNA expression was fitted using compartmental approaches. The transcription rate profile and mRNA degradation parameter was estimated using maximum likelihood method of ADAPT II software.


RESULTS
Data sets containing noise for mRNA levels were simulated for four diverse pharmaceutically relevant conditions: receptor nonlinearity, a model in which the variant mRNAs differing in mRNA degradation constants were transcribed and for a minimal model of the cell cycle. SPLINDID was able to fit the data sets and accurately recapitulate the transcription rate profiles normalized to the mRNA degradation rate constants. The model was also challenged using experimental data containing time profiles of cell-cycle-regulated genes.


CONCLUSIONS
The SPLINDID approach is flexible in capturing complicated/complex mRNA profiles that are encountered in many experimental data sets.
Department of Pharmaceutical Sciences, State University of New York at Buffalo, 543 Cooke Hall, Buffalo, New York 14260-1200, USA.
Kavitha
K
Bhasi
Alan
A
Forrest
Murali
M
Ramanathan
D000465:Algorithms; D002453:Cell Cycle / Q000502:physiology; D007700:Kinetics; D008957:Models, Genetic; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D010597:Pharmacogenetics / Q000706:statistics & numerical data*; D012333:RNA, Messenger / Q000096:biosynthesis / Q000235:genetics*; D015398:Signal Transduction / Q000502:physiology; D014158:Transcription, Genetic
D012333:RNA, Messenger