325

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Click the image below to view the animated version of this cover.

Issue 325: Mathematical models of regulatory networks, such as reaction-diffusion models, often require protein copy numbers to constrain them. However, current databases can be scarce, and these quantifications can be costly to obtain. On the flip side, RNA omics datasets are abundant and could be used to predict protein measurements. We developed a tool called Pinferna, which captures these mRNA-to-protein relationships. Interestingly, when applied to breast cancer RNA-seq datasets, inferred copy-number estimates re-classify a large proportion of tumors, suggesting mRNA abundance alone was not sufficient for classification in these samples. This art piece is an abstract representation of RNA-to-protein inference, as the RNA strand slowly morphs to a folded protein structure. The art was made with python code, included code adapted from Artem Kirsanov .