CORN 2.0 - Condition Orientated Regulatory Networks 2.0

Gene regulation is a fundamental process that allows organisms to adapt to their environment and increase complexity through the action of nucleic acid-binding proteins (NBPs), such as transcription factors (TFs), which regulate specific sets of genes under distinct conditions. These regulatory interactions form transcriptional regulatory networks (TRNs), which can be further broken down into transcriptional regulatory sub-networks (TRSNs) centered around individual TFs. TRSNs are more stable and practical for analysis, making them ideal for studying gene regulation under specific conditions. Condition-Oriented Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/corn/home) is a comprehensive library of condition-based TRSNs, including those induced by natural compounds, small molecules, drug treatments, and gene perturbations. CORN 2.0 represents a significant update, associating 7540 specific conditions with 71934 TRSNs across 52 human cell lines, involving 542 transcription factors (TFs). Notably, CORN 2.0 includes 1550 natural compound-triggered TRSNs, providing a valuable resource for studying the pharmacological effects of natural products. This study demonstrates the utility of CORN in three key areas: personalized medicine, induced pluripotency transitions, and natural compound-associated pharmacology. By linking specific conditions to their corresponding TRSNs, CORN enables researchers to explore how gene regulatory networks are altered under various conditions, offering insights into disease mechanisms and potential therapeutic interventions.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.04.003
Citations
1
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
4.17
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article

CORN 2.0 - Condition Orientated Regulatory Networks 2.0

Wenbin Deng, Xinying Zhang, Zhuobin Chen, Ricky Wai Tak Leung et al.
1 citations
Computational and Structural Biotechnology Journal
Scientific Computing and Data Management
4.17
article

CORN 2.0 - Condition Orientated Regulatory Networks 2.0

Wenbin Deng, Xinying Zhang, Zhuobin Chen, Ricky Wai Tak Leung, Xueqing Zong, Sheng-Dong HUANG, Ronghua Lin, Yuyun Liang, Jing Qin, Yaohua Hu, Zixin Yang, Xiaosen Jiang
article en
1 citations

Abstract

Gene regulation is a fundamental process that allows organisms to adapt to their environment and increase complexity through the action of nucleic acid-binding proteins (NBPs), such as transcription factors (TFs), which regulate specific sets of genes under distinct conditions. These regulatory interactions form transcriptional regulatory networks (TRNs), which can be further broken down into transcriptional regulatory sub-networks (TRSNs) centered around individual TFs. TRSNs are more stable and practical for analysis, making them ideal for studying gene regulation under specific conditions. Condition-Oriented Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/corn/home) is a comprehensive library of condition-based TRSNs, including those induced by natural compounds, small molecules, drug treatments, and gene perturbations. CORN 2.0 represents a significant update, associating 7540 specific conditions with 71934 TRSNs across 52 human cell lines, involving 542 transcription factors (TFs). Notably, CORN 2.0 includes 1550 natural compound-triggered TRSNs, providing a valuable resource for studying the pharmacological effects of natural products. This study demonstrates the utility of CORN in three key areas: personalized medicine, induced pluripotency transitions, and natural compound-associated pharmacology. By linking specific conditions to their corresponding TRSNs, CORN enables researchers to explore how gene regulatory networks are altered under various conditions, offering insights into disease mechanisms and potential therapeutic interventions.

Computational and Structural Biotechnology JournalVol. 27
BGI Group (China) (CN), Hong Kong Polytechnic University (HK), Sun Yat-sen University (CN), Shenzhen University (CN), University Town of Shenzhen (CN), University of Chinese Academy of Sciences (CN)
Zero hunger
Openalex Percentile: Top 7%
Scientific Computing and Data Management
4.17
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