[Frontiers in Bioscience 7, a126-134, June 1, 2002]


Lei Qian 1, Yunlong Liu 1, Hui Bin Sun 1,2, and Hiroki Yokota 1,2, 3

1 Biomedical Engineering Program, 2 Departments of Anatomy and Cell Biology, and 3 Mechanical Engineering, Indiana University - Purdue University Indianapolis, Indianapolis, IN


1. Abstract
2. Introduction
3. Materials and Methods
3.1. Example 1
3.2. Example 2
4. Results
4. 1. Example 1
4.1.1. Modeling of MMP transcript levels
4.1.2. Sensitivity analysis
4. 2. Example 2
4.2.1. Modeling of a heterogeneous group of transcripts
4.2.2. Variations among genes
4.2.3. Estimation of active cis-acting elements
5. Discussion
6. Future Work
7. Appendix
8. Acknowledgements
9. References


The availability of human genome sequences provides life scientists and biomedical engineers with a challenging opportunity to develop computational and experimental tools for quantitatively analyzing biological processes. In response to a growing need to integrate experimental mRNA expression data with human genome sequences, we present here a unique analysis named "Promoter-Based Estimation (PROBE)" analysis. The PROBE analysis is "systems analysis" of transcriptional processes using control and estimation theories. A linear model was built in order to estimate the mRNA levels of a group of genes from their regulatory DNA sequences. The model was also used to interpret two independent datasets in skeletal tissues. The results demonstrated that the mRNA levels of a family of matrix metalloproteinases can be modeled from a distribution of cis-acting elements on regulatory DNA sequences. The model accurately predicted a stimulatory role of cis-acting elements such as AP1, NFY, PEA3, and Sp1 as well as an inhibitory role of AP2. These predictions are consistent with biological observations, and a specific assay for testing such predictions is proposed. Although eukaryotic transcription is a complex mechanism, the two examples presented here support the potential use of the described analysis for elucidating the functional significance of DNA regulatory elements.