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We developed toxFlow, a web application for omics data enrichment analysis and toxicity prediction. It uses a sequential workflow to predict substance toxicity based on analog data and similarity criteria.

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Area of Science:

  • Toxicology
  • Bioinformatics
  • Computational Chemistry

Background:

  • Omics data analysis is crucial for understanding biological responses to chemical exposure.
  • Predicting chemical toxicity requires robust methodologies integrating diverse data types.
  • Existing methods may lack integrated workflows for enrichment analysis and read-across prediction.

Purpose of the Study:

  • To introduce toxFlow, a novel web application for omics data enrichment analysis and read-across toxicity prediction.
  • To provide a sequential workflow for filtering omics data and predicting toxicity using analog information.
  • To enable multiperspective characterization of nanoparticles and their toxicological profiles.

Main Methods:

  • Developed a web application, toxFlow, integrating enrichment analysis and correlation-based read-across techniques.
  • Utilized enrichment scores for filtering omics data.
  • Employed physicochemical and biological similarity criteria for selecting analog compounds, particularly for nanoparticles.
  • Integrated embedded or in-house gene signature libraries for enrichment analysis.

Main Results:

  • toxFlow facilitates a sequential workflow for toxicity prediction.
  • The application enables the prediction of toxicity for diverse chemical entities, with a focus on nanoparticles.
  • Interactive visualization tools are provided for exploring data correlations.
  • Results are exportable for further downstream analysis.

Conclusions:

  • toxFlow offers an integrated platform for omics data analysis and toxicity prediction.
  • The application supports a data-driven approach to chemical safety assessment, particularly for complex agents like nanoparticles.
  • toxFlow enhances the prediction of chemical toxicity by leveraging analog data and similarity measures.