ArticleDatabase : the journal of biological databases and curation2015
EcoliNet: a database of cofunctional gene network for Escherichia coli.
Article in Database : the journal of biological databases and curation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 42 citations in OpenAlex.
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- Integration of probabilistic functional networks without an external Gold Standard.BMC bioinformatics · 2022Article
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- Computational Network Inference for Bacterial Interactomics.mSystems · 2022Review
- PangenomeNet: a pan-genome-based network reveals functional modules on antimicrobial resistome for Escherichia coli strains.BMC bioinformatics · 2021Article
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- BiomeNet: a database for construction and analysis of functional interaction networks for any species with a sequenced genome.Bioinformatics (Oxford, England) · 2020Article
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- The y-ome defines the 35% of Escherichia coli genes that lack experimental evidence of function.Nucleic acids research · 2019Article
- A Genome-Scale Co-Functional Network ofMolecules and cells · 2019Article
- Network-based genetic investigation of virulence-associated phenotypes in methicillin-resistant Staphylococcus aureus.Scientific reports · 2018Article
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- PoplarGene: poplar gene network and resource for mining functional information for genes from woody plants.Scientific reports · 2016Article
- Network-assisted investigation of virulence and antibiotic-resistance systems in Pseudomonas aeruginosa.Scientific reports · 2016Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellular processes have been discovered through research on this bacterium. Although much basic research now focuses on more complex model organisms, E. coli still remains important in metabolic engineering and synthetic biology. Despite its long history as a subject of molecular investigation, more than one-third of the E. coli genome has no pathway annotation supported by either experimental evidence or manual curation. Recently, a network-assisted genetics approach to the efficient identification of novel gene functions has increased in popularity. To accelerate the speed of pathway annotation for the remaining uncharacterized part of the E. coli genome, we have constructed a database of cofunctional gene network with near-complete genome coverage of the organism, dubbed EcoliNet. We find that EcoliNet is highly predictive for diverse bacterial phenotypes, including antibiotic response, indicating that it will be useful in prioritizing novel candidate genes for a wide spectrum of bacterial phenotypes. We have implemented a web server where biologists can easily run network algorithms over EcoliNet to predict novel genes involved in a pathway or novel functions for a gene. All integrated cofunctional associations can be downloaded, enabling orthology-based reconstruction of gene networks for other bacterial species as well. Database URL: http://www.inetbio.org/ecolinet.
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