ArticlePLoS computational biology2011
Genetic co-occurrence network across sequenced microbes.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- CORGIAS: identifying correlated gene pairs by considering evolutionary history in a large-scale prokaryotic genome dataset.NAR genomics and bioinformatics · 2025Article
- Functional genomic analysis of genes important for Candida albicans fitness in diverse environmental conditions.Cell reports · 2024Article
- The rhizosphere bacterial community contributes to the nutritional competitive advantage of weedy rice over cultivated rice in paddy soil.BMC microbiology · 2022Article
- Phage defence by deaminase-mediated depletion of deoxynucleotides in bacteria.Nature microbiology · 2022Article
- Inverse Potts model improves accuracy of phylogenetic profiling.Bioinformatics (Oxford, England) · 2022Article
- Undervalued Pseudo-mSphere · 2021Article
- Evidence for Selection in the Abundant Accessory Gene Content of a Prokaryote Pangenome.Molecular biology and evolution · 2021Article
- New Insights into the Co-Occurrences of Glycoside Hydrolase Genes among Prokaryotic Genomes through Network Analysis.Microorganisms · 2021Article
- Coinfinder: detecting significant associations and dissociations in pangenomes.Microbial genomics · 2020Article
- A multi-scale coevolutionary approach to predict interactions between protein domains.PLoS computational biology · 2019Article
- MATria: a unified centrality algorithm.BMC bioinformatics · 2019Article
- Article
- Phylogeny-corrected identification of microbial gene families relevant to human gut colonization.PLoS computational biology · 2018Article
- Testing the Domino Theory of Gene Loss inLife (Basel, Switzerland) · 2018Article
- Taxa-function robustness in microbial communities.Microbiome · 2018Article
- Modules of co-occurrence in the cyanobacterial pan-genome reveal functional associations between groups of ortholog genes.PLoS genetics · 2018Article
- ATria: a novel centrality algorithm applied to biological networks.BMC bioinformatics · 2017Article
- Revised computational metagenomic processing uncovers hidden and biologically meaningful functional variation in the human microbiome.Microbiome · 2017Article
- A set of genes conserved in sequence and expression traces back the establishment of multicellularity in social amoebae.BMC genomics · 2016Article
- Bacterial regulon modeling and prediction based on systematic cis regulatory motif analyses.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The phenotype of any organism on earth is, in large part, the consequence of interplay between numerous gene products encoded in the genome, and such interplay between gene products affects the evolutionary fate of the genome itself through the resulting phenotype. In this regard, contemporary genomes can be used as molecular records that reveal associations of various genes working in their natural lifestyles. By analyzing thousands of orthologs across ∼600 bacterial species, we constructed a map of gene-gene co-occurrence across much of the sequenced biome. If genes preferentially co-occur in the same organisms, they were called herein correlogs; in the opposite case, called anti-correlogs. To quantify correlogy and anti-correlogy, we alleviated the contribution of indirect correlations between genes by adapting ideas developed for reverse engineering of transcriptional regulatory networks. Resultant correlogous associations are highly enriched for physically interacting proteins and for co-expressed transcripts, clearly differentiating a subgroup of functionally-obligatory protein interactions from conditional or transient interactions. Other biochemical and phylogenetic properties were also found to be reflected in correlogous and anti-correlogous relationships. Additionally, our study elucidates the global organization of the gene association map, in which various modules of correlogous genes are strikingly interconnected by anti-correlogous crosstalk between the modules. We then demonstrate the effectiveness of such associations along different domains of life and environmental microbial communities. These phylogenetic profiling approaches infer functional coupling of genes regardless of mechanistic details, and may be useful to guide exogenous gene import in synthetic biology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.