Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error. Academic Article

abstract

• In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

authors

• Dougherty, Edward

published proceedings

• IEEE/ACM Trans Comput Biol Bioinform

altmetric score

• 0.5

author list (cited authors)

• Mohsenizadeh, D. N., Dehghannasiri, R., & Dougherty, E. R.

citation count

• 15

complete list of authors

• Mohsenizadeh, Daniel N||Dehghannasiri, Roozbeh||Dougherty, Edward R

publication date

• January 2018

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE/ACM Transactions on Computational Biology and Bioinformatics  Journal

keywords

• Computer Simulation
• Gene Regulatory Networks
• Models, Biological
• Research Design
• Scientific Experimental Error
• Systems Biology

Digital Object Identifier (DOI)

• 10.1109/TCBB.2016.2602873

start page

• 218

end page

• 230

volume

• 15

issue

• 1

URL

• http://dx.doi.org/10.1109/tcbb.2016.2602873