ArticleACS omega2022
Comprehensive Evaluation and Comparison of Machine Learning Methods in QSAR Modeling of Antioxidant Tripeptides.
Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 48 citations in OpenAlex.
- Explainable Artificial Intelligence to Unveil Patterns of Antioxidant Peptides for Free Radical Regulation.Journal of chemical information and modeling · 2026Article
- Interpretable machine learning framework for peptide lead optimization in ultralarge design spaces.npj drug discovery · 2026Article
- Role of Plant-Derived Antioxidants in Oxidative Stress-Associated Myocardial Infarction: Structure-Activity Relationship (SAR)-Based Mechanistic Insights.Molecules (Basel, Switzerland) · 2026Review
- RLAnOxPeptide: an integrated framework combining transformer and reinforcement learning for efficient antioxidant peptide prediction and innovative design.Bioinformatics (Oxford, England) · 2026Article
- Machine learning-based design, screening, and activity validation of topoisomerase I inhibitors.Molecular diversity · 2026Article
- Machine learning classification of early-stage Parkinson's disease using sit-to-walk biomechanical features.Scientific reports · 2026Article
- Enhancing cancer drug discovery: QSAR modeling with machine learning and chemical representations.PloS one · 2026Article
- Exploring the molecular interaction of bioactive peptides with antioxidative, antidiabetic and anti-inflammatory attributes from sheep milk fermented with lactobacillus and yeast.Scientific reports · 2025Article
- Antioxidant activity at the molecular level: exploring ways of action and computational tools to investigate them.Chemical science · 2025Review
- Predicting the Toxicity of Drug Molecules with Selecting Effective Descriptors Using a Binary Ant Colony Optimization (BACO) Feature Selection Approach.Molecules (Basel, Switzerland) · 2025Article
- Target fishing: from "needle in haystack" to "precise guidance"--new technology, new strategy and new opportunity.Frontiers in pharmacology · 2025Review
- Evaluation of Machine Learning Based QSAR Models for the Classification of Lung Surfactant Inhibitors.Environment & health (Washington, D.C.) · 2024Article
- Predicting antioxidant activity of compounds based on chemical structure using machine learning methods.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2024Article
- Antioxidant Properties of Hemp Proteins: From Functional Food to Phytotherapy and Beyond.Molecules (Basel, Switzerland) · 2022Review
- Convolutional Neural Network Model Based on 2D Fingerprint for Bioactivity Prediction.International journal of molecular sciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to their multiple beneficial effects, antioxidant peptides have attracted increasing interest. Currently, the screening and identification of bioactive peptides, including antioxidative peptides based on wet-chemistry methods are time-consuming and highly rely on many advanced instruments and trained personnel. Quantitative structure-activity relationship (QSAR) analysis as an
Identifiers
What OpenQuestion holds
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.