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Related Experiment Video

Updated: Aug 29, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

PGRNIG: novel parallel gene regulatory network identification algorithm based on GPU.

Bin Yang¹, Wenzheng Bao², Baitong Chen³

¹School of Information Science and Engineering, Zaozhuang University, Zaozhuang 277160, China.

Briefings in Functional Genomics

|September 6, 2022

Summary

This summary is machine-generated.

This study introduces PGRNIG, a parallel algorithm for gene regulatory network inference. It accurately identifies complex gene interactions in biological systems, offering a significant computational speed-up.

Keywords:

S-system Swarm intelligent algorithm compute unified device architecture gene expression gene regulatory networks

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Area of Science:

Computational Biology
Systems Biology
Bioinformatics

Background:

Understanding complex life phenomena requires analyzing gene interactions.
Gene expression data is crucial for inferring gene regulatory networks (GRNs).
The S-system is effective for small GRNs but struggles with larger, complex networks.

Purpose of the Study:

To develop a novel parallel algorithm, PGRNIG, for optimizing S-system parameters.
To improve the accuracy and efficiency of GRN inference for medium-to-large scale networks.

Main Methods:

Proposed PGRNIG algorithm, a parallel swarm intelligent approach.
Enhanced Whale Optimization Algorithm (CWOA) using clone selection.
Parallel CWOA (PCWOA) leveraging CUDA for computational efficiency.
Decomposition strategy and L1 regularization to reduce search space and complexity.

Main Results:

PGRNIG demonstrated superior accuracy in inferring GRNs compared to state-of-the-art methods.
Significant computational speed-up was achieved using the parallel approach.
CWOA and PCWOA exhibited faster convergence than the standard Whale Optimization Algorithm (WOA).

Conclusions:

PGRNIG is an effective and efficient method for GRN inference.
The developed parallel algorithm advances the analysis of complex biological systems.
Findings highlight the potential of swarm intelligence in computational biology.