Rui Jiang

Related Projects

• RegFM: an interpretable context-aware foundation model for human transcriptional regulation
• scMTG reconstructs single-cell temporal dynamics with Markov transition generators
• CREATE: cell-type-specific cis-regulatory elements identification via discrete embedding
• EpiGePT: a pretrained transformer-basedlanguage model for context-specific humanepigenomics
• DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction
• Deep generative modeling and clustering of single cell Hi-C data
• HiChIPdb: a comprehensive database of HiChIP regulatory interactions
• DualGCN: a dual graph convolutional network model to predict cancer drug response
• scGraph: a graph neural network-based approach to automatically identify cell types
• DeepCAGE: Incorporating Transcription Factors in Genome-Wide Prediction of Chromatin Accessibility
• OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions
• Simultaneous deep generative modelling and clustering of single-cell genomic data
• Density estimation using deep generative neural networks
• DeepCDR: a hybrid graph convolutional network for predicting cancer drug response
• EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information
• hicGAN infers super resolution Hi-C data with generative adversarial networks
• DeepHistone: a deep learning approach to predicting histone modifications
• Chromatin accessibility prediction via a hybrid deep convolutional neural network
• A sequence-based method to predict the impact of regulatory variants using random forest