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EvoGenomics.AI is a network for AI applications in evolutionary genomics kindly funded by Imperial College London, CNRS and TUM.

DNADNA (Deep Neural Architecture for DNA) provide utility functions to improve development of neural networks for population genetics. DNADNA should allow researchers to focus on their research project, be it the analysis of population genetic data or building new methods, without the need to focus on proper development methodology (unit test, continuous integration, documentation, etc.). Results will thus be more easily reproduced and shared. Having a common interface will also decrease the risk of bugs.
 

A beta version is available at https://gitlab.com/mlgenetics/dnadna with full documentation at https://mlgenetics.gitlab.io/dnadna/index.html
 

Our groups also developed additional implementations, namely ImaGene  and BaSe  which have been applied to detect positive and balancing selection, respectively.