A multiple regression approach for building genetic networks
Refereed conference paper presented and published in conference proceedings


Times Cited
Altmetrics Information
.

Other information
AbstractThe construction of genetic regulatory networks from time series gene expression data is an important research topic in bioinformatics as large amounts of quantitative gene expression data can be routinely generated nowadays. One of the main difficulties in building such genetic networks is that the data set has huge number of genes but small number of time points. In this paper, we propose a linear regression model for uncovering the relations among the genes by using multiple regression method with filtering. The model takes into account of the fact that real biological networks have the scale-free property. Based on this property and the statistical tests, a filter can be constructed and the interactions among the genes can be inferred by minimizing the distance between the observed data and the predicted data. Numerical examples based on yeast gene expression data are given to demonstrate our method. © 2008 IEEE.
All Author(s) ListZhang S.-Q., Ching W.-K., Tsing N.-K., Leung H.-Y., Guo D.D.
Name of ConferenceBioMedical Engineering and Informatics: New Development and the Future - 1st International Conference on BioMedical Engineering and Informatics, BMEI 2008
Start Date of Conference27/05/2008
End Date of Conference30/05/2008
Place of ConferenceSanya, Hainan
Country/Region of ConferenceChina
Year2008
Month9
Day18
Volume Number1
Pages18 - 23
ISBN9780769531182
ISSN1948-2914
LanguagesEnglish-United Kingdom

Last updated on 2020-19-05 at 00:49