State-Feedback Control of Partially-Observed Boolean Dynamical Systems Using RNA-Seq Time Series Data Conference Paper

abstract

• 2016 American Automatic Control Council (AACC). External control of a genetic regulatory network is used for the purpose of avoiding undesirable states, such as those associated with disease. This paper proposes a strategy for state-feedback infinite-horizon control of Partially-Observed Boolean Dynamical Systems (POBDS) using a single time series of Next-Generation Sequencing (NGS) RNA-seq data. A separation principle is assumed, whereby first the optimal stationary policy is obtained offline by solving Bellman's equation, and then an optimal MMSE observer, the Boolean Kalman Filter, is employed for online implementation of the policy using the RNA-seq observations of the evolving system. Performance is investigated using a Boolean network model of the mutated mammalian cell cycle and simulated RNA-seq observations.

name of conference

• 2016 American Control Conference (ACC)

authors

• Braga Neto, Ulisses

published proceedings

• 2016 AMERICAN CONTROL CONFERENCE (ACC)

altmetric score

• 3

author list (cited authors)

• Imani, M., & Braga-Neto, U.

citation count

• 24

complete list of authors

• Imani, Mahdi||Braga-Neto, Ulisses

publication date

• January 2016

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Proceedings of the ... American Control Conference. American Control Conference  Journal

keywords

• Boolean Dynamical Systems
• Boolean Kalman Filter
• Next-generation Sequencing
• State-feedback Control

Digital Object Identifier (DOI)

• 10.1109/acc.2016.7524920

International Standard Book Number (ISBN) 13

• 9781467386821

start page

• 227

end page

• 232

volume

• 2016-July

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Facc.2016.7524920