DocumentCode :
1502350
Title :
Evaluation of Design Strategies for Time Course Experiments in Genetic Networks: Case Study of the XlnR Regulon in Aspergillus niger
Author :
Omony, Jimmy ; Mach-Aigner, Astrid R. ; De Graaff, Leo H. ; Van Straten, Gerrit ; Van Boxtel, Anton J B
Author_Institution :
Syst. & Control Group, Wageningen Univ., Wageningen, Netherlands
Volume :
9
Issue :
5
fYear :
2012
Firstpage :
1316
Lastpage :
1325
Abstract :
One of the challenges in genetic network reconstruction is finding experimental designs that maximize the information content in a data set. In this paper, the information value of mRNA transcription time course experiments was used to compare experimental designs. The study concerns the dynamic response of genes in the XlnR regulon of Aspergillus niger, with the goal to find the best moment in time to administer an extra pulse of inducing D-xylose. Low and high D-xylose pulses were used to perturb the XlnR regulon. Evaluation of the experimental methods was based on simulation of the regulon. Models that govern the regulation of the target genes in this regulon were used for the simulations. Parameter sensitivity analysis, the Fisher Information Matrix (FIM) and the modified E-criterion were used to assess the design performances. The results show that the best time to give a second D-xylose pulse is when the D-xylose concentration from the first pulse has not yet completely faded away. Due to the presence of a repression effect the strength of the second pulse must be optimized, rather than maximized. The results suggest that the modified E-criterion is a better metric than the sum of integrals of absolute sensitivity for comparing alternative designs.
Keywords :
RNA; bioinformatics; genetics; molecular biophysics; sensitivity analysis; sugar; Aspergillus niger; Fisher information matrix; XlnR regulon; bioinformatics; genetic network reconstruction; mRNA transcription time course experiments; modified E-criterion; parameter sensitivity analysis; second D-xylose pulse; Bioinformatics; Covariance matrix; Data models; Gene expression; Proteins; Sensitivity; Aspergillus niger.; Experimental design strategies; XlnR regulon; genetic network; parameter estimation; time course data; trigger experiments; Aspergillus niger; Computer Simulation; Fungal Proteins; Gene Expression Regulation, Fungal; Gene Regulatory Networks; RNA, Messenger; Regulon; Transcription, Genetic; Xylose;
fLanguage :
English
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
1545-5963
Type :
jour
DOI :
10.1109/TCBB.2012.59
Filename :
6189310
Link To Document :
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