bowang-lab / BIONIC
Biological Network Integration using Convolutions
☆60Updated last year
Alternatives and similar repositories for BIONIC:
Users that are interested in BIONIC are comparing it to the libraries listed below
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆50Updated 3 years ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆47Updated 2 weeks ago
- Knowledge-primed neural networks☆35Updated last year
- Discovering novel cell types across heterogenous single-cell experiments☆121Updated 2 years ago
- Cell2Sentence turns scRNA-seq data into text for LLM training.☆84Updated 4 months ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆28Updated 2 months ago
- spatial transcriptome, single cell☆66Updated last year
- repository containing analysis scripts and auxiliary files☆30Updated 4 years ago
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 3 years ago
- Single-cell multi-omics integration using Optimal Transport☆41Updated 4 months ago
- SIMBA: SIngle-cell eMBedding Along with features☆57Updated 3 months ago
- ☆73Updated last year
- ☆36Updated 2 years ago
- ☆27Updated 3 weeks ago
- CellBox: Interpretable Machine Learning for Perturbation Biology☆54Updated last year
- single cell foundation model for Gene network inference and more☆40Updated this week
- An accurate and efficient deep learning method for single-cell RNA-seq data imputation☆87Updated 2 years ago
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆110Updated 4 months ago
- Diffusion model for gene regulatory network inference.☆16Updated 7 months ago
- ☆26Updated last year
- Interpretation by Deep Generative Masking for Biological Sequences☆37Updated 3 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆93Updated 5 months ago
- Create cell sentences from sequencing data☆21Updated 5 months ago
- ☆56Updated 4 months ago
- ☆24Updated 4 years ago
- TCRconv is a deep learning model for predicting recognition between T cell receptors and epitopes. It uses protBERT embeddings for the TC…☆23Updated 2 years ago
- A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.☆54Updated 9 months ago
- ☆33Updated 2 years ago
- A Python toolkit for setting up benchmarking dataset using biomedical networks☆21Updated 3 weeks ago
- Unsupervised cell functional annotation for single-cell RNA-Seq☆22Updated 2 years ago