marakeby / pnet_prostate_paperLinks
P-NET, Biologically informed deep neural network for prostate cancer classification and discovery
☆163Updated 4 years ago
Alternatives and similar repositories for pnet_prostate_paper
Users that are interested in pnet_prostate_paper are comparing it to the libraries listed below
Sorting:
- Gene2Vec: Distributed Representation of Genes Based on Co-Expression☆125Updated 3 years ago
- Deep-Learning framework for multi-omic and survival data integration☆86Updated last year
- MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations☆90Updated last year
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 3 years ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆51Updated 3 months ago
- ☆56Updated 3 years ago
- ☆56Updated 3 years ago
- Code for evaluating single cell foundation models scBERT and scGPT☆46Updated last year
- Framework for Interpretable Neural Networks☆111Updated 8 months ago
- ☆64Updated 4 months ago
- Deep learning-based tissue compositions and cell-type-specific gene expression analysis with tissue-adaptive autoencoder (TAPE)☆56Updated last year
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆53Updated 3 years ago
- Models and datasets for perturbational single-cell omics☆168Updated 3 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆119Updated last year
- An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.☆160Updated 3 years ago
- Multi-omics integration method using AE and GCN☆38Updated 2 years ago
- UCE is a zero-shot foundation model for single-cell gene expression data☆231Updated 9 months ago
- ☆85Updated 3 months ago
- ☆87Updated last year
- scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks☆153Updated last year
- Deep Learning Methods for Parsing T-Cell Receptor Sequencing (TCRSeq) Data☆122Updated 2 months ago
- Repository for Nicheformer: a foundation model for single-cell and spatial omics☆131Updated 2 weeks ago
- ☆66Updated 2 years ago
- CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis☆35Updated 3 years ago
- Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network☆106Updated 2 years ago
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆156Updated 9 months ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆131Updated 10 months ago
- Transformer for One-Stop Interpretable Cell-type Annotation☆146Updated last year
- ☆43Updated 5 months ago
- ☆339Updated last year