PyTorch Connectomics: segmentation toolbox for EM connectomics
- computer-vision
- neuroscience
- connectomics
- pytorch
Repository Index
47,133 repositories indexed
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Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk
- cancer-imaging-research
- radiomics
- radiomics-features
- machine-learning
Probabilistic cell segmentation for in situ spatial transcriptomics
:triangular_ruler: Orthogonal polynomials in all shapes and sizes.
- python
- mathematics
- engineering
- physics
A Python interface to access neuroanatomical atlases
- neuroscience
- python
- microscopy
- registration
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
Repository for Nicheformer: a foundation model for single-cell and spatial omics
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
- disentanglement
- drug-discovery
- genomics
- perturbation
Python package for image-based profiling
- cytominer
- microscopy
- morphological-profiling
- python
The RAW JavaScript library to work with polynomials
- polynomials
- math
- javascript
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
BulkFormer: A large-scale foundation model for human bulk transcriptomes
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
- r
- neuroanatomy-toolbox
- cran
- neuron
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
- deep-generative-model
- deep-learning
- single-cell-data-integration
- single-cell-multiomics
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
- epigenomics
- pattern-search
- data-visualization
- interactive-machine-learning
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
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.
- single-cell
- scrna-seq
- scatac-seq
- deep-neural-networks
MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
NASA/JPL SPICE Toolkit for C – patched for cross-platform compatibility
- astronomy
- astronomical-algorithms
- celestial-mechanics
- nasa
Multigrate: multiomic data integration for single-cell genomics