Deep learning: new computational modelling techniques for genomics
Citations
579 citations
Cites methods from "Deep learning: new computational mo..."
...These datasets have powered ML models that aim to learn predictive representations of functional DNA and predict genome-wide biochemical profiles in contexts for which experimental data is unavailable (Ching et al., 2018; Eraslan et al., 2019; Libbrecht & Noble, 2015)....
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391 citations
Cites methods from "Deep learning: new computational mo..."
...DL depends on algorithms for reasoning process simulation and data mining, or for developing abstractions [17]....
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239 citations
207 citations
Cites background or methods from "Deep learning: new computational mo..."
...based modelling of data sets (generative models), and using retraining predictors used in one area by new data from another area (transfer learning) have only recently been applied in genomics (14)....
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...Recent advances in the analysis of human genetic variation data in biomedicine and healthcare further increase the appeal of this approach for the design of beneficial mutations (12-14)....
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171 citations
References
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