Bhasi Kavitha, Forrest Alan, Ramanathan Murali
Department of Pharmaceutical Sciences, State University of New York at Buffalo, 14260-1200, USA.
Bioinformatics. 2005 Oct 15;21(20):3873-9. doi: 10.1093/bioinformatics/bti624. Epub 2005 Aug 11.
To evaluate a semi-parametric, model-based approach for obtaining transcription rates from mRNA and protein expression.
The transcription profile input was modeled using an exponential function of a cubic spline and the dynamics of translation; mRNA and protein degradation were modeled using the Hargrove-Schmidt model. The transcription rate profile and the translation, and mRNA and protein degradation rate constants were estimated by the maximum likelihood method.
Simulated datasets generated from the stochastic, transit compartment and dispersion signaling models were used to test the approach. The approach satisfactorily fit the mRNA and protein data, and accurately recapitulated the parameter and the normalized transcription rate profile values. The approach was successfully used to model published data on tyrosine aminotransferase pharmacodynamics.
The semi-parametric approach is effective and could be useful for delineating the genomic effects of drugs.
Code suitable for use with the ADAPT software program is available from the corresponding author.
评估一种基于模型的半参数方法，用于从mRNA和蛋白质表达中获取转录速率。
转录谱输入采用三次样条的指数函数和翻译动力学进行建模；mRNA和蛋白质降解采用Hargrove-Schmidt模型进行建模。转录速率谱以及翻译、mRNA和蛋白质降解速率常数通过最大似然法进行估计。
使用从随机、转运室和扩散信号模型生成的模拟数据集来测试该方法。该方法令人满意地拟合了mRNA和蛋白质数据，并准确再现了参数和标准化转录速率谱值。该方法成功用于对已发表的酪氨酸转氨酶药效学数据进行建模。
半参数方法有效，可能有助于描绘药物的基因组效应。
可从通讯作者处获得适用于ADAPT软件程序的代码。
