Biology
Global parameter estimation for thermodynamic models of transcriptional regulation
Document Type
Article
Abstract
Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. © 2013 Elsevier Inc.
Publication Title
Methods
Publication Date
7-15-2013
Volume
62
Issue
1
First Page
99
Last Page
108
ISSN
1046-2023
DOI
10.1016/j.ymeth.2013.05.012
Keywords
Covariance matrix adaptation-evolutionary strategy, gene regulation, Nelder-Mead simplex method, parameter estimation, Quasi-Newton method, thermodynamic modeling
Repository Citation
Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M.; Sinha, Saurabh; and Arnosti, David N., "Global parameter estimation for thermodynamic models of transcriptional regulation" (2013). Biology. 127.
https://commons.clarku.edu/faculty_biology/127
