ArticleFrontiers in pharmacology2016
A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts.
Article in Frontiers in pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- A multi-dimensional computational framework of drug-induced hepatotoxicity: integrating molecular structure features with disease pathogenesis.Briefings in bioinformatics · 2025Article
- A methotrexate labelled dual metal oxide nanocomposite for long-lasting anti-cancer theranostics.Materials today. Bio · 2025Article
- Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study.International journal of molecular sciences · 2024Review
- Exploring molecular fingerprints of different drugs having bile interaction: a stepping stone towards better drug delivery.Molecular diversity · 2024Article
- Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells.Journal of chemical information and modeling · 2023Article
- Mechanism-driven modeling of chemical hepatotoxicity using structural alerts and an in vitro screening assay.Journal of hazardous materials · 2022Article
- VenomPred: A Machine Learning Based Platform for Molecular Toxicity Predictions.International journal of molecular sciences · 2022Article
- Machine Learning Models for Predicting Liver Toxicity.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets.International journal of molecular sciences · 2021Article
- Prediction and mechanistic analysis of drug-induced liver injury (DILI) based on chemical structure.Biology direct · 2021Article
- Herb-Induced Liver Injury: Phylogenetic Relationship, Structure-Toxicity Relationship, and Herb-Ingredient Network Analysis.International journal of molecular sciences · 2019Review
- An In Silico Model for Predicting Drug-Induced Hepatotoxicity.International journal of molecular sciences · 2019Article
- Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs.Scientific reports · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides
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.