Abstract
In this work, we pose the problem of gene regulatory function identification using a new general framework based on function separation. We prove the uniqueness of the solution within this framework in an almost always sense. Additionally, we develop an iterative scheme, called iterative function separation (IFS), which is guaranteed to converge to a solution. Both these results together guarantee the computation of the unique solution. We also develop theoretical limits on the number of gene expression level measurements (time samples) sufficient to uniquely reconstruct the network. The proposed method (IFS) is validated using synthetic networks both within and outside of the modeling domain of the new framework.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the IEEE Conference on Decision and Control |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 133-138 |
| Number of pages | 6 |
| Volume | 2016-February |
| ISBN (Print) | 9781479978861 |
| DOIs | |
| State | Published - Feb 8 2016 |
| Event | 54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan Duration: Dec 15 2015 → Dec 18 2015 |
Other
| Other | 54th IEEE Conference on Decision and Control, CDC 2015 |
|---|---|
| Country | Japan |
| City | Osaka |
| Period | 12/15/15 → 12/18/15 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization
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Cite this
Bhushan, P., Chang, Y. H., & Tomlin, C. J. (2016). Iterative function separation for gene regulatory function identification. In Proceedings of the IEEE Conference on Decision and Control (Vol. 2016-February, pp. 133-138). [7402098] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2015.7402098