An autoencoder-based platform merges nine gene embedding types into one 512-dimensional representation, with a permutation-adjusted SVCCA analysis showing the sources are largely complementary.
Translating embeddings for modeling multi- relational data.Advances in neural information processing systems, 26, 2013
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Platform for Representation and Integration of multimodal Molecular Embeddings
An autoencoder-based platform merges nine gene embedding types into one 512-dimensional representation, with a permutation-adjusted SVCCA analysis showing the sources are largely complementary.