ArticleProceedings of the National Academy of Sciences of the United States of America2002
Genome-wide coexpression dynamics: theory and application.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 1 of them a synthesis that pooled it.
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Who cites it
103 citing papers in PubMed, 1 synthesis or guideline pooled it, 200 citations in OpenAlex.
- A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide.Bioinformatics (Oxford, England) · 2009Pooled it
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- scCOSMIX: A Mixed-Effects Framework for Differential Coexpression and Transcriptional Interactions Modeling in Single-Cell RNA-Seq.Statistics in medicine · 2025Article
- Time-coexpress: temporal trajectory modeling of dynamic gene co-expression patterns using single-cell transcriptomics data.BMC bioinformatics · 2025Article
- Dissecting genetic regulation of metabolic coordination.Briefings in bioinformatics · 2025Article
- A dynamic co-expression approach reveals Gins2 as a potential upstream modulator of HNSCC metastasis.Scientific reports · 2025Article
- Method of moments framework for differential expression analysis of single-cell RNA sequencing data.Cell · 2024Article
- S100a9 might act as a modulator of the Toll-like receptor 4 transduction pathway in chronic rhinosinusitis with nasal polyps.Scientific reports · 2024Article
- Dissecting gene expression heterogeneity: generalized Pearson correlation squares and theJournal of the American Statistical Association · 2024Article
- Genome-wide search algorithms for identifying dynamic gene co-expression via Bayesian variable selection.Statistics in medicine · 2023Article
- Review
- Flexible copula model for integrating correlated multi-omics data from single-cell experiments.Biometrics · 2023Article
- Generalized Liquid Association Analysis for Multimodal Data Integration.Journal of the American Statistical Association · 2023Article
- Modeling dynamic correlation in zero-inflated bivariate count data with applications to single-cell RNA sequencing data.Biometrics · 2022Article
- NetGAM: Using generalized additive models to improve the predictive power of ecological network analyses constructed using time-series data.ISME communications · 2022Article
- Novel insight into pancreatic adenocarcinoma pathogenesis using liquid association analysis.BMC medical genomics · 2022Article
- Discovery of putative tumor suppressors from CRISPR screens reveals rewired lipid metabolism in acute myeloid leukemia cells.Nature communications · 2021Article
- Nkx3-1 and Fech genes might be switch genes involved in pituitary non-functioning adenoma invasiveness.Scientific reports · 2021Article
- CAMPAREE: a robust and configurable RNA expression simulator.BMC genomics · 2021Article
- MODEL FREE ESTIMATION OF GRAPHICAL MODEL USING GENE EXPRESSION DATA.The annals of applied statistics · 2021Article
43 more citing papers are in PubMed but not listed here.
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1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput expression profiling enables the global study of gene activities. Genes with positively correlated expression profiles are likely to encode functionally related proteins. However, all biological processes are interlocked, and each protein may play multiple cellular roles. Thus the coexpression of any two functionally related genes may depend on the constantly varying, yet often-unknown cellular state. To initiate a systematic study on this issue, a theory of coexpression dynamics is presented. This theory is used to rationalize a strategy of conducting a genome-wide search for the most critical cellular players that may affect the coexpression pattern of any two genes. In one example, using a yeast data set, our method reveals how the enzymes associated with the urea cycle are expressed to ensure proper mass flow of the involved metabolites. The correlation between ARG2 and CAR2 is found to change from positive to negative as the expression level of CPA2 increases. This delicate interplay in correlation signifies a remarkable control on the influx and efflux of ornithine and reflects well the intrinsic cellular demand for arginine. In addition to the urea cycle, our examples include SCH9 and CYR1 (both implicated in a recent longevity study), cytochrome c1 (mitochondrial electron transport), calmodulin (main calcium-binding protein), PFK1 and PFK2 (glycolysis), and two genes, ECM1 and YNL101W, the functions of which are newly revealed. The complexity in computation is eased by a new result from mathematical statistics.
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