ArticleCommunications biology2022
Protein-protein interaction and non-interaction predictions using gene sequence natural vector.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- PPIscreenML is a method for structure-based screening of protein-protein interactions using AlphaFold.eLife · 2026Article
- Article
- Integrated in silico and in vitro evaluation of cocoa pod husk as potential anticancer agents against hepatocellular carcinoma.Molecular biology reports · 2026Article
- Predicting Protein-Protein Interactions by Convolutional Neural Network Model.Biotech (Basel (Switzerland)) · 2026Article
- MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models.BMC biology · 2025Article
- ESM2_AMP: an interpretable framework for protein-protein interactions prediction and biological mechanism discovery.Briefings in bioinformatics · 2025Article
- Topology-driven negative sampling enhances generalizability in protein-protein interaction prediction.Bioinformatics (Oxford, England) · 2025Article
- EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals.Nature communications · 2025Article
- Protein-protein interaction prediction using bidirectional GRUs with explicit ensemble.PloS one · 2025Article
- Accurate Prediction of Protein-Binding Residues in Protein Sequences Using SCRIBER.Methods in molecular biology (Clifton, N.J.) · 2025Article
- TPepPro: a deep learning model for predicting peptide-protein interactions.Bioinformatics (Oxford, England) · 2024Article
- Topological links in predicted protein complex structures reveal limitations of AlphaFold.Communications biology · 2023Article
- SVSBI: sequence-based virtual screening of biomolecular interactions.Communications biology · 2023Article
- Prediction of the tetramer protein complex interaction based on CNN and SVM.Frontiers in genetics · 2023Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Predicting protein-protein interaction and non-interaction are two important different aspects of multi-body structure predictions, which provide vital information about protein function. Some computational methods have recently been developed to complement experimental methods, but still cannot effectively detect real non-interacting protein pairs. We proposed a gene sequence-based method, named NVDT (Natural Vector combine with Dinucleotide and Triplet nucleotide), for the prediction of interaction and non-interaction. For protein-protein non-interactions (PPNIs), the proposed method obtained accuracies of 86.23% for Homo sapiens and 85.34% for Mus musculus, and it performed well on three types of non-interaction networks. For protein-protein interactions (PPIs), we obtained accuracies of 99.20, 94.94, 98.56, 95.41, and 94.83% for Saccharomyces cerevisiae, Drosophila melanogaster, Helicobacter pylori, Homo sapiens, and Mus musculus, respectively. Furthermore, NVDT outperformed established sequence-based methods and demonstrated high prediction results for cross-species interactions. NVDT is expected to be an effective approach for predicting PPIs and PPNIs.
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