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There are many different kinds of "gene regulatory networks", so how to model them with gene expression data depends on what you're trying to model and what type of regulatory mechanisms you want to study. Pick a random gene in the human genome and use a resource database like StringDB. Let's take the TET1 protein for example. Some edges in that ...


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This is an incomplete answer since it's not my field of expertise, but it sounds like Weighted correlation network analysis is what you are referring to. There is a paper which describes how it can be applied to gene expression data. Langfelder, P., Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008). ...


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