ArticleFrontiers in chemistry2020
Exploring the Use of Compound-Induced Transcriptomic Data Generated From Cell Lines to Predict Compound Activity Toward Molecular Targets.
Article in Frontiers in chemistry, 2020. 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.
- Harnessing AI to fuse phenotypic signatures for drug target identification: progress in computational modeling.Briefings in bioinformatics · 2026Review
- In Silico Identification of Natural-Product Aromatase (CYP19A1) Inhibitors via Integrated Molecular Docking and QSAR Modelling.Bioinformatics and biology insights · 2026Article
- The OASIS Consortium: integrating multi-omics technologies to transform chemical safety assessment.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Targeting Prostate Cancer Metabolism Through Transcriptional and Epigenetic Modulation: A Multi-Target Approach to Therapeutic Innovation.International journal of molecular sciences · 2025Review
- Optimizing Cancer Treatment: Exploring the Role of AI in Radioimmunotherapy.Diagnostics (Basel, Switzerland) · 2025Review
- Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping.Toxicological sciences : an official journal of the Society of Toxicology · 2024Article
- Computational pipeline predicting cell death suppressors as targets for cancer therapy.iScience · 2024Article
- Cell Painting-based bioactivity prediction boosts high-throughput screening hit-rates and compound diversity.Nature communications · 2024Article
- Benchmarking causal reasoning algorithms for gene expression-based compound mechanism of action analysis.BMC bioinformatics · 2023Article
- Application of perturbation gene expression profiles in drug discovery-From mechanism of action to quantitative modelling.Frontiers in systems biology · 2023Review
- Predicting molecular initiating events using chemical target annotations and gene expression.BioData mining · 2022Article
- Computational analyses of mechanism of action (MoA): data, methods and integration.RSC chemical biology · 2022Review
- A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease.eLife · 2022Article
- Recent advances in drug repurposing using machine learning.Current opinion in chemical biology · 2021Review
- Exploration of the DARTable Genome- a Resource Enabling Data-Driven NAMs for Developmental and Reproductive Toxicity Prediction.Frontiers in toxicology · 2021Article
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
Pharmaceutical or phytopharmaceutical molecules rely on the interaction with one or more specific molecular targets to induce their anticipated biological responses. Nonetheless, these compounds are also prone to interact with many other non-intended biological targets, also known as off-targets. Unfortunately, off-target identification is difficult and expensive. Consequently, QSAR models predicting the activity on a target have gained importance in drug discovery or in the de-risking of chemicals. However, a restricted number of targets are well characterized and hold enough data to build such
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.