ArticleBMC bioinformatics2021
GENPPI: standalone software for creating protein interaction networks from genomes.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 7 citations in OpenAlex.
- In vitro effects of Bacillus velezensis strain Mandacaium against Xanthomonas citri pv. glycines: genomic and metabolomic insights.Scientific reports · 2026Article
- In silico interactome analysis reveals distinct and complementary metabolic roles of bacteria in stingless bee larval food.Computational and structural biotechnology journal · 2026Article
- Improving protein interaction prediction in GenPPi: a novel interaction sampling approach preserving network topology.BMC bioinformatics · 2025Article
- Beyond Methane Oxidation: The Protein Landscape of ANME-2a Reveals an Integrated System for Diazotrophy and Membrane Fortification.Environmental microbiology reports · 2025Article
- Using Phylogeny and a Conserved Genomic Neighborhood Analysis to Extract and Visualize Gene Sets Involved in Target Gene Function: The Case of [NiFe]-hydrogenase and Succinate Dehydrogenase.Microbes and environments · 2025Article
- Article
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
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Authors and funding
4 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundBacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships capable of being annotated only from genomes are conserved gene neighbourhoods (CNs), phylogenetic profiles (PPs), and gene fusions. At present, there is no standalone software that enables networks of interactions among proteins to be created using these three evolutionary characteristics with efficient and effective results.
resultsWe developed GENPPI software for the ab initio prediction of interaction networks using predicted proteins from a genome. In our case study, we employed 50 genomes of the genus Corynebacterium. Based on the PP relationship, GENPPI differentiated genomes between the ovis and equi biovars of the species Corynebacterium pseudotuberculosis and created groups among the other species analysed. If we inspected only the CN relationship, we could not entirely separate biovars, only species. Our software GENPPI was determined to be efficient because, for example, it creates interaction networks from the central genomes of 50 species/lineages with an average size of 2200 genes in less than 40 min on a conventional computer. Moreover, the interaction networks that our software creates reflect correct evolutionary relationships between species, which we confirmed with average nucleotide identity analyses. Additionally, this software enables the user to define how he or she intends to explore the PP and CN characteristics through various parameters, enabling the creation of customized interaction networks. For instance, users can set parameters regarding the genus, metagenome, or pangenome. In addition to the parameterization of GENPPI, it is also the user's choice regarding which set of genomes they are going to study.
conclusionsGENPPI can help fill the gap concerning the considerable number of novel genomes assembled monthly and our ability to process interaction networks considering the noncore genes for all completed genome versions. With GENPPI, a user dictates how many and how evolutionarily correlated the genomes answer a scientific query.
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