ArticlePharmaceuticals (Basel, Switzerland)2022
MPMABP: A CNN and Bi-LSTM-Based Method for Predicting Multi-Activities of Bioactive Peptides.
Article in Pharmaceuticals (Basel, Switzerland), 2022. 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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17 citing papers in PubMed, 44 citations in OpenAlex.
- SA-MTP: a structure-aware framework for multifunctional therapeutic peptide annotation.Briefings in bioinformatics · 2026Article
- The Use of DeepQSAR Models for the Discovery of Peptides With Enhanced Antimicrobial and Antibiofilm Potential.Molecular informatics · 2026Article
- Artificial intelligence in functional food innovation: Bioactive enhancement and formulation optimization: A quasi-systematic review.Food chemistry: X · 2026Review
- Harnessing Machine Learning Approaches for the Identification, Characterization, and Optimization of Novel Antimicrobial Peptides.Antibiotics (Basel, Switzerland) · 2025Review
- Accurate structure-activity relationship prediction of antioxidant peptides using a multimodal deep learning framework.Journal of cheminformatics · 2025Article
- Multi-feature fusion network with marginal focal dice loss for multi-label therapeutic peptide prediction.PLoS computational biology · 2025Article
- BPFun: a deep learning framework for bioactive peptide function prediction using multi-label strategy by transformer-driven and sequence rich intrinsic information.BMC bioinformatics · 2025Article
- MultiPep-DLCL: recognition of multifunctional therapeutic peptides through deep learning with label-sequence contrastive learning.Briefings in bioinformatics · 2025Article
- AMHF-TP: Multifunctional therapeutic peptides prediction based on multi-granularity hierarchical features.Quantitative biology (Beijing, China) · 2025Article
- MFP-MFL: Leveraging Graph Attention and Multi-Feature Integration for Superior Multifunctional Bioactive Peptide Prediction.International journal of molecular sciences · 2025Article
- Advances of deep Neural Networks (DNNs) in the development of peptide drugs.Future medicinal chemistry · 2025Review
- iMFP-LG: Identify Novel Multi-functional Peptides Using Protein Language Models and Graph-based Deep Learning.Genomics, proteomics & bioinformatics · 2025Article
- Designing novel peptides with amyloid-Frontiers in artificial intelligence · 2025Article
- Research Progress of Food-Derived Antihypertensive Peptides in Regulating the Key Factors of the Renin-Angiotensin System.Nutrients · 2024Review
- CELA-MFP: a contrast-enhanced and label-adaptive framework for multi-functional therapeutic peptides prediction.Briefings in bioinformatics · 2024Article
- Machine learning tools for peptide bioactivity evaluation - Implications for cell culture media optimization and the broader cultivated meat industry.Current research in food science · 2024Article
- Toxicity of Glycyl-l-Prolyl-l-Glutamate Pseudotripeptides: Cytotoxic, Oxidative, Genotoxic, and Embryotoxic Perspectives.Journal of toxicology · 2022Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Bioactive peptides are typically small functional peptides with 2-20 amino acid residues and play versatile roles in metabolic and biological processes. Bioactive peptides are multi-functional, so it is vastly challenging to accurately detect all their functions simultaneously. We proposed a convolution neural network (CNN) and bi-directional long short-term memory (Bi-LSTM)-based deep learning method (called MPMABP) for recognizing multi-activities of bioactive peptides. The MPMABP stacked five CNNs at different scales, and used the residual network to preserve the information from loss. The empirical results showed that the MPMABP is superior to the state-of-the-art methods. Analysis on the distribution of amino acids indicated that the lysine preferred to appear in the anti-cancer peptide, the leucine in the anti-diabetic peptide, and the proline in the anti-hypertensive peptide. The method and analysis are beneficial to recognize multi-activities of bioactive peptides.
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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.