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Not sure what to do with Regulator Effects and Interaction Networks in IPA? After you conduct an IPA Core Analysis on your ‘omic dataset (RNA-seq, scRNA-seq, proteomics, metabolomics and more), start using the Regulator Effects and Interaction Networks results to interpret your data and generate hypotheses.
We’ll cover:
- Regulator Effects: These causal and directional networks connect major regulators with downstream diseases and biological functions
- Interaction Networks: These networks focus on the interconnectivity of molecules (genes, proteins, metabolites etc.) in your dataset
By tv.qiagenbioinformatics.comNot sure what to do with Regulator Effects and Interaction Networks in IPA? After you conduct an IPA Core Analysis on your ‘omic dataset (RNA-seq, scRNA-seq, proteomics, metabolomics and more), start using the Regulator Effects and Interaction Networks results to interpret your data and generate hypotheses.
We’ll cover:
- Regulator Effects: These causal and directional networks connect major regulators with downstream diseases and biological functions
- Interaction Networks: These networks focus on the interconnectivity of molecules (genes, proteins, metabolites etc.) in your dataset