ToxiTaRGET: a multi-omics resource for toxicant-responsive molecular targets
Kumar, R.; Fu, T.; Kuntala, P. K.; Fu, S.; Li, D.; Bartolomei, M. S.; Walker, C. L.; Wang, T.; Zhang, B. A.
Show abstract
Environmental toxicant exposures can induce widespread alterations in both the transcriptome and epigenome of mammals, and directly contribute to the increased risk of various diseases, including cardiovascular disorders, cancer, and neurological disorders. To evaluate how early-life toxicants produce long-term impacts on the transcriptome and epigenome in mice, the Toxicant Exposures and Responses by Genomic and Epigenomic Regulators of Transcription II (TaRGET II) Consortium generated a landmark resource comprising 3,607 multi-omics from longitudinal studies in mice. The molecular changes in responding to distinct environmental toxicants, including arsenic (As), lead (Pb), bisphenol A (BPA), tributyltin (TBT), di-2-ethylhexyl phthalate (DEHP), dioxin (TCDD), and fine particulate matter (PM2.5), were systematically identified and visualized on an integrative platform, ToxiTaRGET, to allow quickly search and browse by researchers. ToxiTaRGET houses a rich repository of molecular signatures, including gene expression, chromatin accessibility, and DNA methylation profiles, in response to early-life toxicant exposures. These molecular signatures span multiple biologically important tissues in both male and female mice at three distinct life stages, offering a valuable resource for the environmental health and toxicogenomic research communities.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Benchmarking of a Bayesian single cell RNAseq differential gene expression test for dose-response study designs. 94%
- Chemoenzymatic labeling of DNA methylation patterns for single-molecule epigenetic mapping 91%
- NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders 91%
Similar papers in this journal
- A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes 92%
- NanoLoop: A deep learning framework leveraging Nanopore sequencing for chromatin loop prediction 90%
- Chronic opioid treatment arrests neurodevelopment and alters synaptic activity in human midbrain organoids 90%
Similar papers in this journal
- PIP-Seq identifies novel heterogeneous lung innate lymphocyte population activation after combustion product exposure 92%
- Longitudinal Saliva Omics Responses to Immune Perturbation: A Case Study 91%
- Mouse pulmonary pathological characteristics induced by Asian-mineral dust transported with Coniothyrium fuckelii at a high altitude of 2,000 meters 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.