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Updated: Jan 19, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

SoyCSN: Soybean context-specific network analysis and prediction based on tissue-specific transcriptome data.

Juexin Wang^1,2, Md Shakhawat Hossain^2,3, Zhen Lyu¹

¹Department of Electrical Engineering and Computer Science University of Missouri St. Louis MO USA.

|September 25, 2019

Summary

This summary is machine-generated.

Researchers developed Soybean context-specific networks (SoyCSN) to map gene expression in soybean tissues. This resource aids in understanding tissue-specific gene regulation and relationships, benefiting soybean research and breeding.

Keywords:

RNA‐seq context‐specific network database interactome soybean

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Last Updated: Jan 19, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

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Published on: June 17, 2012

Author Spotlight: Soybean Hairy Root Transformation for the Analysis of Gene Function

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Published on: May 5, 2023

Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants

Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants

Published on: August 5, 2020

Area of Science:

Genomics and Bioinformatics
Plant Molecular Biology
Systems Biology

Background:

The Soybean Gene Atlas project generated extensive RNA-Seq data for major soybean tissues.
Understanding tissue-specific gene expression is crucial for soybean improvement.

Purpose of the Study:

To develop a computational pipeline for inferring Soybean context-specific networks (SoyCSN).
To analyze, annotate, retrieve, and visualize soybean gene networks at transcriptome and interactome levels.
To provide insights into tissue-specific gene regulatory mechanisms and relationships.

Main Methods:

Applied BicMix and Cross-Conditions Cluster Detection algorithms for module detection based on co-expression.
Predicted context-specific interactomes by integrating soybean tissue gene expression and protein-protein interaction data.
Conducted functional analyses of predicted networks to identify tissue specificities.

Main Results:

Developed SoyCSN, a computational pipeline for soybean network inference.
Identified tissue-specific gene expression modules and interactomes.
Highlighted functional connections, such as photosynthesis and symbiosis in soybean leaf networks.

Conclusions:

SoyCSN provides a valuable resource for exploring soybean gene regulatory mechanisms.
The interactive web service within SoyKB facilitates systematic exploration of context specificities.
This work supports soybean researchers and molecular breeders in understanding gene relationships.