ArticleiScience2024
An ensemble deep learning model for predicting minimum inhibitory concentrations of antimicrobial peptides against pathogenic bacteria.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Artificial intelligence catalyzes antimicrobial peptide design.Synthetic and systems biotechnology · 2027Review
- QMAP: a benchmark for standardized evaluation of antimicrobial peptide MIC and hemolytic activity regression.Scientific reports · 2026Article
- Metabolism-Based Biomarkers for Rapid Phenotypic Antibiotic Susceptibility Testing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- ANIA: an inception-attention network for predicting minimum inhibitory concentration of antimicrobial peptides.Briefings in bioinformatics · 2026Article
- Antimicrobial Peptides Against Antimicrobial-Resistant Bacteria: Focus on Machine Learning.Infection and drug resistance · 2026Review
- Integrative computational-experimental discovery and translation of antifungal peptides for multidrug-resistant fungi.Frontiers in microbiology · 2026Review
- tsAMP: a strain-level antimicrobial peptide identification framework based on large language models and pathogen genomic variation.Frontiers in microbiology · 2026Article
- Lab to codes: multimodel advanced AI-driven pipelines to drive antimicrobial peptide design for the post-antibiotic era.Frontiers in cellular and infection microbiology · 2026Review
- Harnessing Machine Learning Approaches for the Identification, Characterization, and Optimization of Novel Antimicrobial Peptides.Antibiotics (Basel, Switzerland) · 2025Review
- Detecting antibiotic resistance: classical, molecular, advanced bioengineering, and AI-enhanced approaches.Frontiers in microbiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rise of antibiotic resistance necessitates effective alternative therapies. Antimicrobial peptides (AMPs) are promising due to their broad inhibitory effects. This study focuses on predicting the minimum inhibitory concentration (MIC) of AMPs against whom-priority pathogens:
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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.