openalexZenodo (CERN European Organization for Nuclear Research)
Data used in "Multi-omics integration and batch correction using a modality-agnostic deep learning framework"
Jose Ignacio Alvira Larizgoitia, Gabriele Partel, Jelle Jacobs, Alejandro Sifrim
These are multimodal dataset objects and trained model parameters used in the study. The files are organized in pairs, where each multimodal dataset (.h5mu file) corresponds to a trained model parameter file (.pt) generated using the MIMA (Multimodal Integration with Modality-agn…
Also available via: European Organization for Nuclear Research