Transcription factor interactome analysis was performed on the Metacore platform (MetaCore+MetaDrug® version 20.3 build 70200, Clarivate, London, UK) using the list of DEGs obtained by a fold change cutoff of 1.4 with a padj < 0.05. We have used this approach previously [15 (link),52 (link)]. Transcription factors were not directly measured in our data but inferred from gene expression signatures based on an unbiased predictive analysis of known upstream regulators of DEGs. The transcriptional regulators of DEGs were ranked by a Z-score cut-off of 2.0 with a p-adj < 0.05. Comparisons were made between shNT 5% CO2 vs. shNT 10% CO2, shNT 5% CO2 +LPS vs. shNT 10% CO2 +LPS, shNR4A2 5% CO2 +LPS vs. shNR4A2 10% CO2 +LPS, shNR4A3 5% CO2+LPS vs. shNR4A3 10% CO2 +LPS. Supplementary Table S5 .
Metacore metadrug
Manufactured by Clarivate
MetaCore+MetaDrug® is a computational biology platform that provides access to a comprehensive knowledge base of molecular interactions and biological processes. It enables the analysis and interpretation of high-throughput experimental data, such as gene expression, proteomics, and metabolomics.
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Lab products found in correlation
2 protocols using metacore metadrug
1
Transcription Factor Interactome Analysis of DEGs
2
In Silico Pharmacokinetics of Compound 2C
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To investigate of in silico pharmacokinetic profiles of compound 2C, the MetaCore/MetaDrug platform from Clarivate Analytics was used 40 . MetaCore/MetaDrug uses binary QSAR models for the prediction of the pharmacokinetic properties. The prediction of a therapeutic activity or toxic effect using recursive partitioning algorithm is calculated based on the ChemTree ability to correlate structural descriptors to that property. These pharmacokinetic properties successfully investigated the predicted toxicityand adsorption, distribution, metabolism, excretion (ADME) of compound 2C.
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