A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression da

Background: Proteins are the primary regulatory agents of transcription even though mRNA expression data alone, from systems like DNA microarrays, are widely used. In addition, the regulation process in genetic systems is inherently non-linear in nature, and most studies employ a time-course analysis of mRNA expression. These considerations should be taken into account in the development of methods for the inference of regulatory interactions in genetic networks. Results: We use an S-system based model for the transcription and translation process. We propose an optimizationbased regulatory network inference approach that uses time-varying data from DNA microarray analysis. Currently, this seems to be the only model-based method that can be used for the analysis of time-course "relative" expressions (expression ratios). We perform an analysis of the dynamic behavior of the system when the number of experimental samples available is varied, when there are different levels of ...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Reuben Thomas, Carlos J. Paredes, Sanjay Mehrotra, Vassily Hatzimanikatis, Eleftherios T. Papoutsakis
• Keywords: BMCBI 2007, DNA Microarray, Mrna Expression, Primary Regulatory Agents