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Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors

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Published on: August 18, 2023

Optimized network inference for immune diseased single cells.

Elena Merino Tejero¹, Dwain Jude Vaz¹, Guillermo Barturen^2,3,4

¹Systems Biology Ireland, School of Medicine, University College Dublin, Dublin, Ireland.

Frontiers in Immunology

|August 8, 2025

Summary

ONIDsc, a new model, identifies four key genes in systemic lupus erythematosus (SLE) patients by analyzing single-cell data. This regulatory network inference tool advances understanding of immune cell dysfunction in SLE.

Keywords:

Systemic lupus erythematosus (SLE)gene marker mathematical modeling network inference single-cell

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Area of Science:

Computational biology
Immunology
Systems biology

Background:

Autoimmune disorders like systemic lupus erythematosus (SLE) are complex and heterogeneous.
Understanding immune system mechanisms in SLE requires high-resolution approaches.

Purpose of the Study:

To introduce ONIDsc, a single-cell regulatory network inference model.
To elucidate immune-related disease mechanisms in SLE using high-dimensional single-cell data.

Main Methods:

ONIDsc enhances the Generalized Lasso Granger (GLG) causality model.
Optimal lambda penalty is determined using cyclical coordinate descent.
ONIDsc was benchmarked against existing models using ChIP-seq and ChIP-chip data.

Main Results:

ONIDsc outperformed existing methods when validated against gold standards.
Applied to control and SLE patient datasets, ONIDsc reconstructed immune cell networks.
Four gene transcripts (MXRA8, NADK, POLR3GL, UBXN11) were identified in SLE patients but not controls.

Conclusions:

The identified genes are linked to pathways involved in immune regulation.
ONIDsc is a powerful tool for dissecting physiological and pathological processes in immune cells.
ONIDsc facilitates high-resolution mechanistic studies in complex diseases like SLE.