Iterative function separation for gene regulatory function identification

Palak Bhushan, Young Hwan Chang, Claire J. Tomlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Decision and Control
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-138
Number of pages6
Volume2016-February
ISBN (Print)9781479978861
DOIs
StatePublished - Feb 8 2016
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Other

Other54th IEEE Conference on Decision and Control, CDC 2015
CountryJapan
CityOsaka
Period12/15/1512/18/15

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