https://www.cell.com/cell/fulltext/S0092-8674(19)30547-1 … Graph Laplacian eigenvector embeddings of pairwise "distances" between genes can recover the spatial configuration of DNA in cells. A very practical application of my original field of study, manifold learning.
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https://blogs.sciencemag.org/pipeline/archives/2019/06/27/a-completely-new-way-to-picture-dna-in-cells … @Dereklowe explains the biology succinctly here. Genes are "close" spatially if cDNA primers attached to each of them interact, which will show up in PCR. This means you can infer the shape of the DNA without any optical microscopy at all!
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