ArticleGigaScience2020
TinderMIX: Time-dose integrated modelling of toxicogenomics data.
Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Review on Predictive Models and Integration Strategies for Holistic Impact Assessment of Chemicals and Materials.Environmental science & technology · 2026Review
- Endothelial sensitivity to pro-fibrotic signals links systemic exposure to pulmonary fibrosis.Cell death & disease · 2025Article
- Investigating the dependency of in vitro benchmark concentrations on exposure time in transcriptomics experiments.Toxicology in vitro : an international journal published in association with BIBRA · 2024Article
- The Effect of Historical Data-Based Informative Prior on Benchmark Dose Estimation of Toxicogenomics.Chemical research in toxicology · 2023Article
- Advancing chemical safety assessment through an omics-based characterization of the test system-chemical interaction.Frontiers in toxicology · 2023Article
- Candidate biomarkers and persistent transcriptional responses after low and high dose ionizing radiation at high dose rate.International journal of radiation biology · 2023Article
- Characterization of ENM Dynamic Dose-Dependent MOA in Lung with Respect to Immune Cells Infiltration.Nanomaterials (Basel, Switzerland) · 2022Article
- Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation.Briefings in bioinformatics · 2022Article
- The potential of a data centred approach & knowledge graph data representation in chemical safety and drug design.Computational and structural biotechnology journal · 2022Review
- Supervised Methods for Biomarker Detection from Microarray Experiments.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Emerging Bioinformatics Methods and Resources in Drug Toxicology.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Nextcast: A software suite to analyse and model toxicogenomics data.Computational and structural biotechnology journal · 2022Article
- Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials.Scientific data · 2021Article
- TinderMIX: Time-dose integrated modelling of toxicogenomics data.GigaScience · 2020Article
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Authors and funding
7 authors.
Funding
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Abstract
backgroundOmics technologies have been widely applied in toxicology studies to investigate the effects of different substances on exposed biological systems. A classical toxicogenomic study consists in testing the effects of a compound at different dose levels and different time points. The main challenge consists in identifying the gene alteration patterns that are correlated to doses and time points. The majority of existing methods for toxicogenomics data analysis allow the study of the molecular alteration after the exposure (or treatment) at each time point individually. However, this kind of analysis cannot identify dynamic (time-dependent) events of dose responsiveness.
resultsWe propose TinderMIX, an approach that simultaneously models the effects of time and dose on the transcriptome to investigate the course of molecular alterations exerted in response to the exposure. Starting from gene log fold-change, TinderMIX fits different integrated time and dose models to each gene, selects the optimal one, and computes its time and dose effect map; then a user-selected threshold is applied to identify the responsive area on each map and verify whether the gene shows a dynamic (time-dependent) and dose-dependent response; eventually, responsive genes are labelled according to the integrated time and dose point of departure.
conclusionsTo showcase the TinderMIX method, we analysed 2 drugs from the Open TG-GATEs dataset, namely, cyclosporin A and thioacetamide. We first identified the dynamic dose-dependent mechanism of action of each drug and compared them. Our analysis highlights that different time- and dose-integrated point of departure recapitulates the toxicity potential of the compounds as well as their dynamic dose-dependent mechanism of action.
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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.