ArticleFrontiers in pharmacology2018
Using Machine Learning to Predict Synergistic Antimalarial Compound Combinations With Novel Structures.
Article in Frontiers in pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 42 citations in OpenAlex.
- Systematic modeling predicts synergistic and safe drug combinations for parasitic diseases.PLoS neglected tropical diseases · 2026Article
- Machine Learning for Multi-Target Drug Discovery: Challenges and Opportunities in Systems Pharmacology.Pharmaceutics · 2025Review
- Novel Antibacterial Approaches and Therapeutic Strategies.Antibiotics (Basel, Switzerland) · 2025Review
- Advances in artificial intelligence-based technologies for increasing the quality of medical products.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2024Review
- Antiprotozoal peptide prediction using machine learning with effective feature selection techniques.Heliyon · 2024Article
- Antimalarial Drug Combination Predictions Using the Machine Learning Synergy Predictor (MLSyPred©) tool.Acta parasitologica · 2024Article
- Molecular Descriptors Property Prediction Using Transformer-Based Approach.International journal of molecular sciences · 2023Article
- Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development.International journal of molecular sciences · 2023Review
- CDCDB: A large and continuously updated drug combination database.Scientific data · 2022Article
- Prediction of Synergistic Antibiotic Combinations by Graph Learning.Frontiers in pharmacology · 2022Article
- Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions.Medicinal research reviews · 2021Review
- Artificial intelligence in drug discovery and development.Drug discovery today · 2021Review
- Prediction of Synergistic Drug Combinations for Prostate Cancer by Transcriptomic and Network Characteristics.Frontiers in pharmacology · 2021Article
- Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases.Frontiers in chemistry · 2021Review
- microRNAs Tune Oxidative Stress in Cancer Therapeutic Tolerance and Resistance.International journal of molecular sciences · 2019Review
- COMBImage2: a parallel computational framework for higher-order drug combination analysis that includes automated plate design, matched filter based object counting and temporal data mining.BMC bioinformatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The parasite
Indexed as
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.