In:
Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 101, No. 44 ( 2004-11-02), p. 15561-15566
Abstract:
Statistical similarity analysis has been instrumental in elucidation of the voluminous microarray data. Genes with correlated expression profiles tend to be functionally associated. However, the majority of functionally associated genes turn out to be uncorrelated. One conceivable reason is that the expression of a gene can be sensitively dependent on the often-varying cellular state. The intrinsic state change has to be plastically accommodated by gene-regulatory mechanisms. To capture such dynamic coexpression between genes, a concept termed “liquid association” (LA) has been introduced recently. LA offers a scoring system to guide a genome-wide search for critical cellular players that may interfere with the coexpression of a pair of genes, thereby weakening their overall correlation. Although the LA method works in many cases, a direct extension to more than two genes is hindered by the “curse of dimensionality.” Here we introduce a strategy of finding an informative 2D projection to generalize LA for multiple genes. A web site is constructed that performs on-line LA computation for any user-specified group of genes. We apply this scoring system to study yeast protein complexes by using the Saccharomyces cerevisiae protein complexes database of the Munich Information Center for Protein Sequences. Human genes are also investigated by profiling of 60 cancer cell lines of the National Cancer Institute. In particular, our system links the expression of the Alzheimer's disease hallmark gene APP (amyloid-β precursor protein) to the β-site-cleaving enzymes BACE and BACE2, the γ-site-cleaving enzymes presenilin 1 and 2, apolipoprotein E, and other Alzheimer's disease-related genes.
Type of Medium:
Online Resource
ISSN:
0027-8424
,
1091-6490
DOI:
10.1073/pnas.0402962101
Language:
English
Publisher:
Proceedings of the National Academy of Sciences
Publication Date:
2004
detail.hit.zdb_id:
209104-5
detail.hit.zdb_id:
1461794-8
SSG:
11
SSG:
12
