Analysis Of Peak-To-Average Power Ratio Of Orthogonal Chirp Division Multiplexing Multicarrier System Based on The Discrete Fractional Cosine Transform
41-46
41.Cnf-571 Paper View Page
Title
An online algorithm for reverse engineering sparse gene regulatory networks using non-linear state-space models
This paper proposes a novel algorithm for inferring gene regulatory
networks which makes use of cubature Kalman filter
(CKF) and Kalman filter (KF) techniques in conjunction with
compressed sensing methods. The gene network is described
using a state-space model. A non-linear model for the evolution
of gene expression is considered, while the gene expression
data is assumed to follow a linear Gaussian model.
The hidden states are estimated using CKF. The system parameters
are modeled as a Gauss-Markov process and are estimated
using compressed sensing based KF. These parameters
provide insight into the regulatory relations among the
genes. The proposed algorithm is evaluated rigorously using
synthetic data as well as the DREAM4 in silico 10 gene data
sets. The proposed algorithm shows superior performance in
terms of accuracy, robustness and scalability.
Track
SPWC: Signal Processing for Wireless Communications
Conference
4th Mosharaka International Conference on Mobile Computing and Wireless Communications (MIC-MCWC 2013)
Congress
2013 Global Congress on Mobile Computing and Wireless Communications (GC-MCWC 2013), 14-16 June 2013, Valencia, Spain
Pages
12-17
Topics
Bioinformatics Biological System Modeling
ISSN
2227-331X
DOI
BibTeX
@inproceedings{571MCWC2013,
title={An online algorithm for reverse engineering sparse gene regulatory networks using non-linear state-space models},
author={Amina Noor, and Erchin Serpedin, and Mohamed Nounou, and Hazem Nounou},
booktitle={2013 Global Congress on Mobile Computing and Wireless Communications (GC-MCWC 2013)},
year={2013},
pages={12-17},
doi={}},
organization={Mosharaka for Research and Studies}
}
