Sparse biologically-constrained optimal perturbation of gene regulatory networks

Haoyu Wang; Nidhal Bouaynaya; Roman Shterenberg; Dan Schonfeld

doi:10.1109/ICASSP.2013.6637834

Sparse biologically-constrained optimal perturbation of gene regulatory networks

Haoyu Wang, Nidhal Bouaynaya, Roman Shterenberg, Dan Schonfeld

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

This paper derives a sparse optimal perturbation of gene regulatory networks by determining the optimal perturbation of the minimal number of individual genes that force the network to settle into desired equilibrium states. Previous efforts have led to intervention in gene regulatory networks by deriving the optimal perturbation of the state probability transition matrix. Current technology in molecular biology, however, is limited to perturbation of the state of individual genes, not the state probability transition matrix. Our computer simulation experiments on the Human melanoma gene regulatory network demonstrate the superiority of the proposed approach to gene regulation in comparison to the previous methods based on the marginal of the optimal perturbation of the probability transition matrix of the network.

Original language	English (US)
Title of host publication	2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages	1167-1171
Number of pages	5
DOIs	https://doi.org/10.1109/ICASSP.2013.6637834
State	Published - Oct 18 2013
Externally published	Yes
Event	2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada Duration: May 26 2013 → May 31 2013

Other

Other	2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/Territory	Canada
City	Vancouver, BC
Period	5/26/13 → 5/31/13

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.2013.6637834

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title = "Sparse biologically-constrained optimal perturbation of gene regulatory networks",

abstract = "This paper derives a sparse optimal perturbation of gene regulatory networks by determining the optimal perturbation of the minimal number of individual genes that force the network to settle into desired equilibrium states. Previous efforts have led to intervention in gene regulatory networks by deriving the optimal perturbation of the state probability transition matrix. Current technology in molecular biology, however, is limited to perturbation of the state of individual genes, not the state probability transition matrix. Our computer simulation experiments on the Human melanoma gene regulatory network demonstrate the superiority of the proposed approach to gene regulation in comparison to the previous methods based on the marginal of the optimal perturbation of the probability transition matrix of the network.",

author = "Haoyu Wang and Nidhal Bouaynaya and Roman Shterenberg and Dan Schonfeld",

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doi = "10.1109/ICASSP.2013.6637834",

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Wang, H, Bouaynaya, N, Shterenberg, R & Schonfeld, D 2013, Sparse biologically-constrained optimal perturbation of gene regulatory networks. in 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings., 6637834, pp. 1167-1171, 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, 5/26/13. https://doi.org/10.1109/ICASSP.2013.6637834

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AU - Bouaynaya, Nidhal

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AU - Schonfeld, Dan

PY - 2013/10/18

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N2 - This paper derives a sparse optimal perturbation of gene regulatory networks by determining the optimal perturbation of the minimal number of individual genes that force the network to settle into desired equilibrium states. Previous efforts have led to intervention in gene regulatory networks by deriving the optimal perturbation of the state probability transition matrix. Current technology in molecular biology, however, is limited to perturbation of the state of individual genes, not the state probability transition matrix. Our computer simulation experiments on the Human melanoma gene regulatory network demonstrate the superiority of the proposed approach to gene regulation in comparison to the previous methods based on the marginal of the optimal perturbation of the probability transition matrix of the network.

AB - This paper derives a sparse optimal perturbation of gene regulatory networks by determining the optimal perturbation of the minimal number of individual genes that force the network to settle into desired equilibrium states. Previous efforts have led to intervention in gene regulatory networks by deriving the optimal perturbation of the state probability transition matrix. Current technology in molecular biology, however, is limited to perturbation of the state of individual genes, not the state probability transition matrix. Our computer simulation experiments on the Human melanoma gene regulatory network demonstrate the superiority of the proposed approach to gene regulation in comparison to the previous methods based on the marginal of the optimal perturbation of the probability transition matrix of the network.

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BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings

T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013

Y2 - 26 May 2013 through 31 May 2013

ER -

Sparse biologically-constrained optimal perturbation of gene regulatory networks

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