Using deep learning to analyze genetic mutations

Full article written by David Beyer can be found here: Deep learning meets genome biology

  • The application of deep learning to genomic medicine is off to a promising start; it could impact diagnostics, intensive care, pharmaceuticals and insurance.
  • The “genotype-phenotype divide”—our inability to connect genetics to disease phenotypes—is preventing genomics from advancing medicine to its potential.
  • Deep learning can bridge the genotype-phenotype divide, by incorporating an exponentially growing amount of data, and accounting for the multiple layers of complex biological processes that relate the genotype to the phenotype.
  • Deep learning has been successful in applications where humans are naturally adept, such as image, text, and speech understanding. The human mind, however, isn’t intrinsically designed to understand the genome. This gap necessitates the application of “super-human intelligence” to the problem.
  • Efforts in this space must account for underlying biological mechanisms; overly simplistic, “black box” approaches will drive only limited value.

(Source: Deep Genomics)

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