NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
- computational-biology
- bioinformatics
- graph-convolution
- deep-learning
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NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
Python package for analysis of multiomic single cell RNA-seq and ATAC-seq.
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
The framework for quantification of neuronal anatomy
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
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High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics
Methods for Image-Based Cell Profiling
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
MCP server for spatial transcriptomics analysis through natural language interfaces.
Predicting Cell Health with Morphological Profiles
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Multigrate: multiomic data integration for single-cell genomics
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
3D shape analysis using deep learning
A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
Single-cell fluorescence microscopy data analysis
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics