
To detect cancer we turned genomes into images and put them through DCNNs - 8iterations
https://medium.com/@leonardvandriel/2d40360fcfcc
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urlwolf
How come this is not bigger news?

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leblancfg
It's the deep learning equivalent of a souped-up Honda Civic. Sure, with
enough tweaking it'll eventually be competitive, but you could have just
bought a racecar.

Variant calling doesn't look like it needs to be turned into a image in the
first place. You'd probably be better off feeding a regular, non-convolutional
network some tabular data.

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malux85
This is right, a convolutoonal network is the right choice for images, but
images are not the right choice for “vectorising” the genomic data, because
vectorising it in a 2D grid and then using a convolutional network on it (a
network designed to exploit spatial hierarchy) is introducing unnecessary and
arbitrary constraints on data locality. Definitely a souped up Honda Civic -
love the metaphor

