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Related Experiment Video

Updated: May 18, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Reverse engineering and analysis of large genome-scale gene networks.

Maneesha Aluru¹, Jaroslaw Zola, Dan Nettleton

¹Department of Genetics, Iowa State University, Ames, IA 50011, USA. aluru@iastate.edu

Nucleic Acids Research

|October 9, 2012

Summary

We developed TINGe, a novel parallel program for fast and accurate whole-genome network reconstruction. This tool enables efficient analysis of large gene expression datasets, overcoming computational limitations of existing methods.

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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

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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

Area of Science:

Computational Biology
Systems Biology
Genomics

Background:

Reconstructing whole-genome networks of complex organisms is challenging due to computational intensity of accurate models.
Existing methods struggle to scale with large gene numbers and expression datasets.

Purpose of the Study:

To develop a fast and accurate method for reverse engineering large-scale gene networks.
To enable scalable analysis of whole-genome regulatory networks.

Main Methods:

Developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program.
Implemented B-spline formulation for linear-time MI computation and a novel direct permutation testing algorithm.
Utilized parallel algorithms to reduce runtime for large network construction.

Main Results:

TINGe successfully reverse-engineered the whole-genome network of Arabidopsis thaliana from 3137 GeneChips in 9 minutes on a 1024-core cluster.
Demonstrated comparable or superior performance against ARACNe and GeneNet.
Developed Gene Network Analyzer (GeNA) for context-specific subnetwork extraction.

Conclusions:

TINGe provides a scalable and efficient solution for whole-genome network reconstruction.
TINGe and GeNA facilitate comprehensive pathway analysis and data accessibility via the web.