AI Article Synopsis
- Visualization and analysis of biological networks are essential for understanding complex living systems, including gene regulatory and metabolic networks, but the diversity and complexity of these networks present significant analytical challenges.
- The iTraNet web application was developed to simplify the analysis of trans-omics networks, revealing that specific molecules in wild-type mice respond to glucose, unlike in certain mutant strains.
- iTraNet is publicly available for use at https://itranet.streamlit.app/, providing researchers with a tool to enhance their insights into biological networks.
Article Abstract
Motivation: Visualization and analysis of biological networks play crucial roles in understanding living systems. Biological networks include diverse types, from gene regulatory networks and protein-protein interactions to metabolic networks. Metabolic networks include substrates, products, and enzymes, which are regulated by allosteric mechanisms and gene expression. However, the analysis of these diverse omics types is challenging due to the diversity of databases and the complexity of network analysis.
Results: We developed iTraNet, a web application that visualizes and analyses trans-omics networks involving four types of networks: gene regulatory networks, protein-protein interactions, metabolic networks, and metabolite exchange networks. Using iTraNet, we found that in wild-type mice, hub molecules within the network tended to respond to glucose administration, whereas in mice, this tendency disappeared. With its ability to facilitate network analysis, we anticipate that iTraNet will help researchers gain insights into living systems.
Availability And Implementation: iTraNet is available at https://itranet.streamlit.app/.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493990 | PMC |
| http://dx.doi.org/10.1093/bioadv/vbae141 | DOI Listing |
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