The Database of Condition Orientated Regulatory Networks

The Database of Condition Orientated Regulatory Networks (CORN) is a library of condition orientated transcriptional regulatory networks (TRNs). A transcriptional regulatory network is a collection of transcription regulators with their associated downstream genes, where the TRNs activated in a cell defines its cell identity and function. In other words, TRNs govern the gene expression in a cell, thus cell statues are programmed by TRNs. By calculating gene regulators and genes with significant expression alterations after specific condition treatments and construct corresponding TRNs and transcriptional regulatory sub-networks (TRSNs), CORN associated 1805 different types of specific conditions (drug treatments) to 9554 TRNs in 25 human cell lines, involving 204 transcription factors (TFs). By linking and curating specific conditions to responsive TRNs, the scientific community can now perceive how TRNs are altered and controlled by conditions alone in an organized manner for the first time. This database will be the foundation and reference material for scientists who aim to control TRNs without traditional genetic engineering approaches, while also provides key resources for the pharmaceutical community to study the relationships between drugs and cell states in terms of gene regulations.


Data collection and arrangement of drug experiments

We have collected a large number of experimental data of molecular disturbance, including experimental conditions, experimental time, concentration of experimental interfering agent, etc

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Differential gene analysis

According to the transcriptome data and the corresponding experimental conditions, we obtained the gene set with significant difference in the expression under these conditions

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Construction of regulatory network

Through further analysis of different genes, we mark the transcription regulatory factors, observe the regulatory relationship between transcription factors and other genes under this condition, and construct corresponding regulatory subsets

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CORN database construction

By sorting out the data of the above steps, we have built a database of condition oriented regulatory networks for query. Users can understand the changes of the regulatory system generated by each small molecule drug and detailed data. This provides convenience for drug treatment and mechanism research

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