✅ 2024 Nature machine intelligence - A transformer-based weakly supervised computational pathology method for clinical-grade diagnosis and molecular marker discovery of gliomas
2024 Nature Methods - scGPT: toward building a foundation model for single-cell multi-omics using generative AI
✅ 2023 Nature - Foundation models for generalist medical artificial intelligence
II. Deep Learning Models for Multi-modal Data
2022 Nature Reviews - Obtaining genetics insights from deep learning via explainable artificial intelligence
2022 Genome Biology - A benchmark study of deep learning‑based multi‑omics data fusion methods for cancer
✅ 2022 Cancer Cell - Pan-cancer integrative histology-genomic analysis via multimodal deep learning
2022 Nature Biotech. - Multi-omics single-cell data integration and regulatory inference with graph-linked embedding
✨ 2021 Nature Communications - MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification
✨ 2021 Bioinformatics - PathCNN: interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma
2021 Nature Machine Intelligence - Integration of multiomics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms
2021 Bioinformatics - Subtype-GAN: a deep learning approach for integrative cancer subtyping of multi-omics data
2018 Clinical Cancer Research - Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer
III. Other Models for Multi-modal Data
2024 Nature Communications - Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights
2023 Nature - Transfer learning enables predictions in network biology
2022 BIB - Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods
✅ 2022 Bioinformatics - MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification
✨ 2022 BIB - A computational framework to unify orthogonal information in DNA methylation and copy number aberrations in cell-free DNA for early cancer detection
2019 Bioinformatics - DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays
2019 Bioinformatics - Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy
IV. More Deep Learning Models
Deep Learning on RNA
3D Structure prediction of RNA: 2021 Science - Geometric deep learning of RNA structure
2D structure (Transfer learning): 2019 Nature Commn. - SPOT-RNA: RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning
RNA/DNA-Protein Binding (DeepBind): 2015 Nature Biotech. - DeepBind: Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
AS of RNA: 2019 Cell - Predicting Splicing from Primary Sequence with Deep Learning
AS of RNA (DARTS): 2019 Nature Methods - Deep-learning augmented RNA-seq analysis of transcript splicing
APA of RNA: 2019 Cell - A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation
Deep Learning on DNA
2022 Nature - The evolution, evolvability and engineering of gene regulatory DNA
Deep Learning on Protein
2022 Nature Biotech. - Using deep learning to annotate the protein universe
AlphaFold2 - 2021 Nature - Highly accurate protein structure prediction with AlphaFold
Baker et al. - 2021 Science - Accurate prediction of protein structures and interactions using a three-track neural network