ArticleBiology2021
ILeukin10Pred: A Computational Approach for Predicting IL-10-Inducing Immunosuppressive Peptides Using Combinations of Amino Acid Global Features.
Article in Biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 26 citations in OpenAlex.
- High-throughput in silico multi-epitope reverse vaccine design against hydatidosis.Scientific reports · 2026Article
- Cytokine-driven immunogenicity prediction: integrating HLA binding and cytokine induction.Briefings in bioinformatics · 2026Article
- Multi-Epitope mRNA Vaccine TargetingBioinformatics and biology insights · 2026Article
- In silico design of novel multi-epitope peptide vaccine against Neospora caninum induced cattle abortion targeting extracellular GRA2 and Nc-p43 protein.Scientific reports · 2025Article
- Immunoinformatics-based strategies for developing DNA and mRNA vaccines against monkeypox virus (MPXV).Virology journal · 2025Article
- Computational Development of Multi-Epitope Reovirus Vaccine with Potent Predicted Binding to TLR2 and TLR4.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Cyclodextrin-AmB-IL-10 antagonist peptide nanoparticles treat leishmaniasis more effectively than conventional AmB.Nanomedicine (London, England) · 2025Article
- Immunoinformatic strategy for developing multi-epitope subunit vaccine against Helicobacter pylori.PloS one · 2025Article
- A multi-epitope vaccine targeting a key virulence factor ClfA: An In-silico approach to combat Staphylococcus aureus infections.PloS one · 2025Article
- A hybrid method for discovering interferon-gamma inducing peptides in human and mouse.Scientific reports · 2024Article
- AntiBP3: A Method for Predicting Antibacterial Peptides against Gram-Positive/Negative/Variable Bacteria.Antibiotics (Basel, Switzerland) · 2024Article
- Peptide discovery across the spectrum of neuroinflammation; microglia and astrocyte phenotypical targeting, mediation, and mechanistic understanding.Frontiers in molecular neuroscience · 2024Review
- StackIL10: A stacking ensemble model for the improved prediction of IL-10 inducing peptides.PloS one · 2024Article
- Deciphering the Immunogenicity of Monkeypox Proteins for Designing the Potential mRNA Vaccine.ACS omega · 2023Article
- C10Pred: A First Machine Learning Based Tool to Predict C10 Family Cysteine Peptidases Using Sequence-Derived Features.International journal of molecular sciences · 2022Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Interleukin (IL)-10 is a homodimer cytokine that plays a crucial role in suppressing inflammatory responses and regulating the growth or differentiation of various immune cells. However, the molecular mechanism of IL-10 regulation is only partially understood because its regulation is environment or cell type-specific. In this study, we developed a computational approach, ILeukin10Pred (interleukin-10 prediction), by employing amino acid sequence-based features to predict and identify potential immunosuppressive IL-10-inducing peptides. The dataset comprises 394 experimentally validated IL-10-inducing and 848 non-inducing peptides. Furthermore, we split the dataset into a training set (80%) and a test set (20%). To train and validate the model, we applied a stratified five-fold cross-validation method. The final model was later evaluated using the holdout set. An extra tree classifier (ETC)-based model achieved an accuracy of 87.5% and Matthew's correlation coefficient (MCC) of 0.755 on the hybrid feature types. It outperformed an existing state-of-the-art method based on dipeptide compositions that achieved an accuracy of 81.24% and an MCC value of 0.59. Our experimental results showed that the combination of various features achieved better predictive performance..
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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.