Hassani, H. and Ghodsi, Z., 2017. Evaluating the analytical distribution of bicoid gene expression profile. Meta Gene, 14 (December), 91-99.
Full text available as:
|
PDF
Metagene2.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 1MB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
DOI: 10.1016/j.mgene.2017.07.014
Abstract
Segmentation in Drosophila melanogaster starts with a key maternal input known as bicoid gene. The initial positional information provided by this gene induces the sequential activation of segmentation network. Therefore, an accurate mathematical model describing the gene expression profile of bicoid gene expects to provide essential insights into the gene cross-regulations presented in that network. The significantly stochastic, highly volatile and non-normal nature of the bicoid gene expression profile encouraged us to look for the best distribution function describing this profile. We exploit the use of fifty-four different powerful and widely-used distributions and conclude that FatigueLife(3P) fits the data more accurately than the other distributions. The reliability and validity of the results are evaluated via both simulation studies and empirical evidence thereby adding more confidence and value to the findings of this research
Item Type: | Article |
---|---|
ISSN: | 2214-5400 |
Uncontrolled Keywords: | Bicoid; Distribution; Drosophila melanogaster; Model; segmentation gene |
Group: | Bournemouth University Business School |
ID Code: | 29704 |
Deposited By: | Symplectic RT2 |
Deposited On: | 11 Oct 2017 14:11 |
Last Modified: | 14 Mar 2022 14:07 |
Downloads
Downloads per month over past year
Repository Staff Only - |