Optimizing bicoid signal extraction
Authors: Hassani, H., Silva, E.S. and Ghodsi, Z.
Journal: Mathematical Biosciences
Volume: 294
Pages: 46-56
eISSN: 1879-3134
ISSN: 0025-5564
DOI: 10.1016/j.mbs.2017.09.008
Abstract:Signal extraction and analysis is of great importance, not only in fields such as economics and meteorology, but also in genetics and even biomedicine. There exists a range of parametric and nonparametric techniques which can perform signal extractions. However, the aim of this paper is to define a new approach for optimising signal extraction from bicoid gene expression profile. Having studied both parametric and nonparametric signal extraction techniques, we identified the lack of specific criteria enabling users to select the optimal signal extraction parameters. Exploiting the expression profile of bicoid gene, which is a maternal segmentation coordinate gene found in Drosophila melanogaster, we introduce a new approach for optimising the signal extraction using a nonparametric technique. The underlying criteria are based on the distribution of the residual, more specifically its skewness.
https://eprints.bournemouth.ac.uk/30069/
Source: Scopus
Optimizing bicoid signal extraction.
Authors: Hassani, H., Silva, E.S. and Ghodsi, Z.
Journal: Math Biosci
Volume: 294
Pages: 46-56
eISSN: 1879-3134
DOI: 10.1016/j.mbs.2017.09.008
Abstract:Signal extraction and analysis is of great importance, not only in fields such as economics and meteorology, but also in genetics and even biomedicine. There exists a range of parametric and nonparametric techniques which can perform signal extractions. However, the aim of this paper is to define a new approach for optimising signal extraction from bicoid gene expression profile. Having studied both parametric and nonparametric signal extraction techniques, we identified the lack of specific criteria enabling users to select the optimal signal extraction parameters. Exploiting the expression profile of bicoid gene, which is a maternal segmentation coordinate gene found in Drosophila melanogaster, we introduce a new approach for optimising the signal extraction using a nonparametric technique. The underlying criteria are based on the distribution of the residual, more specifically its skewness.
https://eprints.bournemouth.ac.uk/30069/
Source: PubMed
Optimizing bicoid signal extraction
Authors: Hassani, H., Silva, E.S. and Ghodsi, Z.
Journal: MATHEMATICAL BIOSCIENCES
Volume: 294
Pages: 46-56
eISSN: 1879-3134
ISSN: 0025-5564
DOI: 10.1016/j.mbs.2017.09.008
https://eprints.bournemouth.ac.uk/30069/
Source: Web of Science (Lite)
Optimizing bicoid signal extraction.
Authors: Hassani, H., Silva, E.S. and Ghodsi, Z.
Journal: Mathematical biosciences
Volume: 294
Pages: 46-56
eISSN: 1879-3134
ISSN: 0025-5564
DOI: 10.1016/j.mbs.2017.09.008
Abstract:Signal extraction and analysis is of great importance, not only in fields such as economics and meteorology, but also in genetics and even biomedicine. There exists a range of parametric and nonparametric techniques which can perform signal extractions. However, the aim of this paper is to define a new approach for optimising signal extraction from bicoid gene expression profile. Having studied both parametric and nonparametric signal extraction techniques, we identified the lack of specific criteria enabling users to select the optimal signal extraction parameters. Exploiting the expression profile of bicoid gene, which is a maternal segmentation coordinate gene found in Drosophila melanogaster, we introduce a new approach for optimising the signal extraction using a nonparametric technique. The underlying criteria are based on the distribution of the residual, more specifically its skewness.
https://eprints.bournemouth.ac.uk/30069/
Source: Europe PubMed Central
Optimizing bicoid signal extraction.
Authors: Hassani, H., Silva, E.S. and Ghodsi, Z.
Journal: Mathematical Biosciences
Volume: 294
Issue: December
Pages: 46-56
ISSN: 0025-5564
Abstract:Signal extraction and analysis is of great importance, not only in fields such as economics and meteorology, but also in genetics and even biomedicine. There exists a range of parametric and nonparametric techniques which can perform signal extractions. However, the aim of this paper is to define a new approach for optimising signal extraction from bicoid gene expression profile. Having studied both parametric and nonparametric signal extraction techniques, we identified the lack of specific criteria enabling users to select the optimal signal extraction parameters. Exploiting the expression profile of bicoid gene, which is a maternal segmentation coordinate gene found in Drosophila melanogaster, we introduce a new approach for optimising the signal extraction using a nonparametric technique. The underlying criteria are based on the distribution of the residual, more specifically its skewness.
https://eprints.bournemouth.ac.uk/30069/
Source: BURO EPrints