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Related Experiment Video

Updated: Sep 11, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

DualNetM: an adaptive dual network framework for inferring functional-oriented markers.

Bingjie Dai¹, Hanshuang Li¹, Peizhuo Wang²

¹State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Institutes of Biomedical Sciences, College of Life Sciences, Inner Mongolia University, Hohhot, 010020, China.

|August 13, 2025

Summary

This summary is machine-generated.

DualNetM, a novel deep generative model, identifies functional gene markers from complex gene regulatory networks (GRNs) using single-cell data. This approach improves understanding of cell identity and development by pinpointing key regulatory genes.

Keywords:

Dual-network framework Functional-oriented markers Gene regulatory network Single-cell data

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Last Updated: Sep 11, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain

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Published on: October 13, 2023

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Area of Science:

Genomics
Computational Biology
Systems Biology

Background:

Gene regulatory networks (GRNs) are crucial for cell identity and development.
Single-cell sequencing technologies enable GRN research but identifying key marker genes is challenging.

Purpose of the Study:

To present DualNetM, a deep generative model for inferring functional-oriented marker genes from GRNs.
To improve the identification of biologically relevant marker genes.

Main Methods:

DualNetM utilizes a dual-network framework with graph neural networks and adaptive attention mechanisms.
It constructs GRNs from single-cell data and integrates gene co-expression networks.
Functional-oriented markers are identified from bidirectional co-regulatory networks.

Main Results:

DualNetM demonstrated superior performance in GRN construction and marker inference compared to benchmarks.
Novel malignant markers associated with lethality were identified in a melanoma dataset.
Stage-specific functional markers were identified in mouse embryonic fibroblast reprogramming, clarifying their roles.

Conclusions:

DualNetM effectively facilitates the inference of functional-oriented markers from complex GRNs.
The model enhances biological relevance in marker identification for developmental and disease studies.