ENCODE Software
All software used or developed by the ENCODE Consortium
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- apricot — sourceapricot implements submodular optimization for the purpose of summarizing massive data sets into minimally redundant subsets that are still representative of the original data. These subsets are useful for both visualizing the modalities in the data and for training accurate machine learning models with just a fraction of the examples and compute.
- Avocado — sourceAvocado is a multi-scale deep tensor factorization method for learning a latent representation of the human epigenome. The purpose of this model is two fold; first, to impute epigenomic experiments that have not yet been performed, and second, to learn a latest representation of the human epigenome that can be used as input for machine learning models in the place of epigenomic data itself.