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Found 4 papers, 2 papers with code
SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival
To mitigate the impact of missing features within the modality on prediction accuracy, we devised a convolutional masked autoencoder (CMAE) to process the heterogeneous graph post-feature reconstruction.
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning
Meanwhile, the ESM-NBR obtains the MCC values for DNA-binding residues prediction of 0. 427 and 0. 391 on two independent test sets, which are 18. 61 and 10. 45% higher than those of the second-best methods, respectively.
PACS: Prediction and analysis of cancer subtypes from multi-omics data based on a multi-head attention mechanism model
Due to the high heterogeneity and clinical characteristics of cancer, there are significant differences in multi-omic data and clinical characteristics among different cancer subtypes.
Robust Blind Source Separation by Soft Decision-Directed Non-Unitary Joint Diagonalization
Approximate joint diagonalization of a set of matrices provides a powerful framework for numerous statistical signal processing applications.
