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iNetModels 2.0: an interactive visualization and database of multi-omics data.

Muhammad Arif1, Cheng Zhang1,2, Xiangyu Li1

  • 1Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm SE-171 21, Sweden.

Nucleic Acids Research
|April 13, 2021
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Summary
This summary is machine-generated.

iNetModels is a new database that links multiple types of biological data (multi-omics) to understand human health and disease. It visualizes these complex biological networks, making them accessible for research.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • Understanding human wellness and disease requires integrating diverse omics data.
  • Existing databases lack comprehensive multi-omics association data.
  • Biological network analysis is crucial for deciphering complex biological processes.

Purpose of the Study:

  • To present iNetModels, an interactive platform for visualizing Multi-Omics Biological Networks (MOBNs).
  • To enable exploration of associations between clinical chemistry, proteomics, metabolomics, and metagenomics data.
  • To provide access to tissue- and cancer-specific Gene Co-expression Networks (GCNs).

Main Methods:

  • Development of an interactive database and visualization platform.
  • Integration of multi-omics data (clinical chemistry, anthropometrics, proteomics, metabolomics, metagenomics) from the same individuals.
  • Inclusion of Gene Co-expression Networks (GCNs) for specific tissues and cancers.

Main Results:

  • iNetModels provides a centralized resource for multi-omics data associations.
  • The platform allows interactive exploration and customization of biological network contexts (e.g., sex-specific).
  • Users can upload and visualize their own MOBNs and GCNs.

Conclusions:

  • iNetModels facilitates research into human wellness and disease by integrating multi-omics data.
  • The platform is accessible to users without bioinformatics expertise.
  • iNetModels is freely available at https://inetmodels.com.