Sciweavers

Share
BMCBI
2007

Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory

9 years 8 days ago
Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory
Background: Large-scale sequencing of entire genomes has ushered in a new age in biology. One of the next grand challenges is to dissect the cellular networks consisting of many individual functional modules. Defining co-expression networks without ambiguity based on genome-wide microarray data is difficult and current methods are not robust and consistent with different data sets. This is particularly problematic for little understood organisms since not much existing biological knowledge can be exploited for determining the threshold to differentiate true correlation from random noise. Random matrix theory (RMT), which has been widely and successfully used in physics, is a powerful approach to distinguish system-specific, non-random properties embedded in complex systems from random noise. Here, we have hypothesized that the universal predictions of RMT are also applicable to biological systems and the correlation threshold can be determined by characterizing the correlation matrix ...
Feng Luo, Yunfeng Yang, Jianxin Zhong, Haichun Gao
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2007
Where BMCBI
Authors Feng Luo, Yunfeng Yang, Jianxin Zhong, Haichun Gao, Latifur Khan, Dorothea K. Thompson, Jizhong Zhou
Comments (0)
books