Bicoid signal extraction with a selection of parametric and nonparametric signal processing techniques.

Ghodsi, Z., Silva, E.S. and Hassani, H., 2015. Bicoid signal extraction with a selection of parametric and nonparametric signal processing techniques. Genomics Proteomics Bioinformatics, 13 (3), 183 - 191.

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DOI: 10.1016/j.gpb.2015.02.006

Abstract

The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraction in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average.

Item Type:Article
Uncontrolled Keywords:Bicoid ; Drosophila melanogaster ; Signal extraction ; Signal processing ; Animals ; Computer Simulation ; Drosophila melanogaster ; Female ; Homeodomain Proteins ; Signal Processing, Computer-Assisted ; Signal-To-Noise Ratio ; Trans-Activators
Group:Faculty of Management
ID Code:29774
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:26 Sep 2017 11:15
Last Modified:26 Sep 2017 11:15

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