ArticleOncotarget2017
Development of estrogen receptor beta binding prediction model using large sets of chemicals.
Article in Oncotarget, 2017. 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
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
15 citing papers in PubMed, 33 citations in OpenAlex.
- Unveiling Novel Metalloprotease Inhibitors Targeting Botulinum Neurotoxin Through Structure-Based Virtual Screening of Drug Libraries and Molecular Dynamics Simulations.International journal of molecular sciences · 2026Article
- Machine Learning and Large Language Models for Modeling Complex Toxicity Pathways and Predicting Steroidogenesis.Environmental science & technology · 2025Article
- Interpretable machine learning models for predicting the antitumor effects of metal and metal oxide nanomaterials.RSC advances · 2025Article
- Unlocking the potential of AI: Machine learning and deep learning models for predicting carcinogenicity of chemicals.Journal of environmental science and health. Part C, Toxicology and carcinogenesis · 2025Review
- Review of machine learning and deep learning models for toxicity prediction.Experimental biology and medicine (Maywood, N.J.) · 2023Review
- Deep Learning Models for Predicting Gas Adsorption Capacity of Nanomaterials.Nanomaterials (Basel, Switzerland) · 2022Article
- Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries.Molecular diversity · 2022Review
- Review ofFrontiers in endocrinology · 2022Review
- Machine learning models for rat multigeneration reproductive toxicity prediction.Frontiers in pharmacology · 2022Article
- Machine Learning Models for Predicting Liver Toxicity.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations.International journal of molecular sciences · 2021Article
- Structure-activity relationship-based chemical classification of highly imbalanced Tox21 datasets.Journal of cheminformatics · 2020Article
- Machine Learning Models for Estrogen Receptor Bioactivity and Endocrine Disruption Prediction.Environmental science & technology · 2020Article
- Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.Molecular pharmaceutics · 2018Article
- Endocrine Disrupting Chemicals Mediated through Binding Androgen Receptor Are Associated with Diabetes Mellitus.International journal of environmental research and public health · 2017Review
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 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We developed an ER
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.