ChihyunPark / DNN_for_ADprediction
☆17Updated 3 years ago
Related projects: ⓘ
- using shallow neural network layer (embedding) to infer gene-gene/sample relationship from gene expression data☆21Updated 5 years ago
- Generative adversarial networks for single-cell RNA-seq imputation☆36Updated 4 years ago
- Code to reproduce results in Ravindra NG* & Sehanobish A* et al. 2020, "Disease State Prediction From Single-Cell Data Using Graph Attent…☆16Updated 4 years ago
- GEDFN: Graph-Embedded Deep Feedforward Network☆23Updated 5 years ago
- ☆60Updated 10 months ago
- Python framework for single-cell RNA-seq clustering with special focus on transfer learning.☆18Updated 5 years ago
- Prediction of mRNA subcellular localization using deep recurrent neural networks☆13Updated 5 years ago
- resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially usin…☆12Updated last year
- Large-scale automatic feature selection for biomarker discovery in high-dimensional OMICs data☆24Updated 5 months ago
- An accurate and efficient deep learning method for single-cell RNA-seq data imputation☆84Updated 2 years ago
- Python 2.7 implementation of network-based stratification (NBS) algorithm from Hofree et al (Nature Methods 2013)☆37Updated 6 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆48Updated 2 years ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆21Updated 2 years ago
- DCAP:Integrating multi-omics data with deep learning for predicting cancer prognosis☆20Updated 3 years ago
- Python Implementation of SIMLR for single-cell visualization and analysis☆22Updated 2 years ago
- Classifying tumor types based on Whole Genome Sequencing (WGS) data☆44Updated 9 months ago
- BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.☆26Updated 4 years ago
- Deep-Learning framework for multi-omic and survival data integration☆74Updated 9 months ago
- Multi-omics integration method using AE and GCN☆28Updated last year
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆55Updated 3 years ago
- ☆47Updated last year
- ☆19Updated 3 years ago
- "DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications", Bioinformatics, Volume 34, Issue 17,☆20Updated 4 years ago
- ☆19Updated 3 years ago
- ☆19Updated last year
- MOLI: Multi-Omics Late Integration with deep neural networks for drug response prediction☆51Updated 3 years ago
- covolutional neural network based coexpression analysis☆72Updated 4 years ago
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆24Updated last year
- Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit☆48Updated last year
- MVP (Qi et al 2021) source code☆15Updated 3 years ago