Bioinformatics | Computational Biology | Genomics A variational autoencoder trained with priors from canonical pathways increases the interpretability of transcriptome data. July 3, 2024
Bioinformatics | Oncology | Pathology Tracing unknown tumor origins with a biological-pathway-based transformer model. June 18, 2024
Bioinformatics | Oncology | Pharmacology Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning. May 9, 2024
Bioinformatics | Clinical Medicine | Proteomics Interpreting biologically informed neural networks for enhanced proteomic biomarker discovery and pathway analysis. September 2, 2023
Bioinformatics | Computational Biology | Oncology A Deep Neural Network for Gastric Cancer Prognosis Prediction Based on Biological Information Pathways. September 20, 2022
Bioinformatics | Cell Biology | Genomics Interpretable Autoencoders Trained on Single Cell Sequencing Data Can Transfer Directly to Data from Unseen Tissues. January 11, 2022
Nutritional Science | Oncology Predicting anticancer hyperfoods with graph convolutional networks. June 8, 2021
Bioinformatics | Deep Learning | Oncology Using Interpretable Deep Learning to Model Cancer Dependencies. May 27, 2021
Bioinformatics | Molecular Biology | Oncology DeepCC: a novel deep learning-based framework for cancer molecular subtype classification. August 22, 2019
Biomedical Informatics | Genomic Medicine | Oncology PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data. January 14, 2019