ArticleBMC systems biology2009
Detecting coordinated regulation of multi-protein complexes using logic analysis of gene expression.
Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- MEAST: a novel framework for analyzing gene set stability in single cell transcriptomics.Scientific reports · 2026Article
- An approach to cellular tropism of SARS-CoV-2 through protein-protein interaction and enrichment analysis.Scientific reports · 2022Article
- Logicome Profiler: Exhaustive detection of statistically significant logic relationships from comparative omics data.PloS one · 2020Article
- Mitoproteomics: Tackling Mitochondrial Dysfunction in Human Disease.Oxidative medicine and cellular longevity · 2018Review
- Differential proteomic and oxidative profiles unveil dysfunctional protein import to adipocyte mitochondria in obesity-associated aging and diabetes.Redox biology · 2017Article
- A Novel Systems-Biology Algorithm for the Analysis of Coordinated Protein Responses Using Quantitative Proteomics.Molecular & cellular proteomics : MCP · 2016Article
- Modeling Gene Networks in Saccharomyces cerevisiae Based on Gene Expression Profiles.Computational and mathematical methods in medicine · 2015Article
- Identification of logic relationships between genes and subtypes of non-small cell lung cancer.PloS one · 2014Article
- Learning transcriptional regulation on a genome scale: a theoretical analysis based on gene expression data.Briefings in bioinformatics · 2012Review
- Phylogenetically informed logic relationships improve detection of biological network organization.BMC bioinformatics · 2011Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMany of the functional units in cells are multi-protein complexes such as RNA polymerase, the ribosome, and the proteasome. For such units to work together, one might expect a high level of regulation to enable co-appearance or repression of sets of complexes at the required time. However, this type of coordinated regulation between whole complexes is difficult to detect by existing methods for analyzing mRNA co-expression. We propose a new methodology that is able to detect such higher order relationships.
resultsWe detect coordinated regulation of multiple protein complexes using logic analysis of gene expression data. Specifically, we identify gene triplets composed of genes whose expression profiles are found to be related by various types of logic functions. In order to focus on complexes, we associate the members of a gene triplet with the distinct protein complexes to which they belong. In this way, we identify complexes related by specific kinds of regulatory relationships. For example, we may find that the transcription of complex C is increased only if the transcription of both complex A AND complex B is repressed. We identify hundreds of examples of coordinated regulation among complexes under various stress conditions. Many of these examples involve the ribosome. Some of our examples have been previously identified in the literature, while others are novel. One notable example is the relationship between the transcription of the ribosome, RNA polymerase and mannosyltransferase II, which is involved in N-linked glycan processing in the Golgi.
conclusionsThe analysis proposed here focuses on relationships among triplets of genes that are not evident when genes are examined in a pairwise fashion as in typical clustering methods. By grouping gene triplets, we are able to decipher coordinated regulation among sets of three complexes. Moreover, using all triplets that involve coordinated regulation with the ribosome, we derive a large network involving this essential cellular complex. In this network we find that all multi-protein complexes that belong to the same functional class are regulated in the same direction as a group (either induced or repressed).
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