Shamir-Lab / Multi-Omics-Cancer-Benchmark
☆26Updated 4 years ago
Alternatives and similar repositories for Multi-Omics-Cancer-Benchmark:
Users that are interested in Multi-Omics-Cancer-Benchmark are comparing it to the libraries listed below
- ☆64Updated last year
- ☆17Updated 5 years ago
- a deep learning approach for integrative cancer subtyping of multi-omics data☆38Updated 9 months ago
- SoptSC for single cell data analysis: unsupervised inference of clustering, cell lineage, pseudotime and cell-cell communication network …☆21Updated 4 years ago
- Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis☆54Updated 3 years ago
- BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.☆29Updated 5 years ago
- Deep Embedding for Single-cell Clustering☆84Updated 10 months ago
- ☆15Updated 3 years ago
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆37Updated 2 years ago
- Enhancing spatial transcriptomics data by predicting the expression of unmeasured genes from a dissociated scRNA-seq data☆33Updated 7 months ago
- GREP: Genome for REPositioning drugs☆40Updated 2 years ago
- ☆53Updated 2 years ago
- overview of spatial datasets☆70Updated last year
- ☆21Updated 8 months ago
- ☆18Updated 3 years ago
- An unsupervised approach for the integrative analysis of single-cell multi-omics data☆28Updated 4 years ago
- Implementations in both Matlab and R of the CIMLR method. The manuscript of the method is available at: https://www.nature.com/articles/s…☆17Updated last year
- Python framework for single-cell RNA-seq clustering with special focus on transfer learning.☆18Updated 5 years ago
- An interpretable deep learning model for cancer classification using high-dimensional omics data☆15Updated 3 years ago
- Similarity Network Fusion☆31Updated 9 years ago
- ☆25Updated 5 years ago
- ☆33Updated 3 years ago
- Spatial cellular architecture predicts prognosis in glioblastoma - Nature Communications☆21Updated last year
- A novel unsupervised batch removal framework, called iMAP, based on neural networks.☆35Updated 3 years ago
- ☆31Updated 5 years ago
- ☆58Updated 4 years ago
- ☆12Updated 2 years ago
- ☆48Updated 3 years ago
- scDeepCluster for Single Cell RNA-seq data☆99Updated 7 months ago
- Classifying tumor types based on Whole Genome Sequencing (WGS) data☆48Updated last year