Computational Biology
Showing 18 of 90 projects
An MCP server that enables natural language conversation for analyzing spatial transcriptomics data through 60+ curated methods.
A machine learning pipeline that predicts 70 cell health phenotypes from Cell Painting image-based morphology profiles.
A Java library for hybrid modeling that combines agent-based and partial differential equation components for complex spatial simulations.
A Python library for integrating multiomic single-cell data using product-of-experts variational autoencoders.
A Python package for 3D single-cell shape analysis using geometric deep learning on point clouds and voxels.
An algorithm that minimizes pixel-dependent noise from sCMOS cameras in microscopy images with arbitrary structures.
A sequential model optimization platform that uses active learning to discover synergistic drug combinations for cancer treatment with minimal screening.
A fast spatial deconvolution tool for transcriptomics data that scales to million-spot datasets while preserving rare cell type signals.
PyTorch implementation of twin graph neural networks with similarity augmentation for drug response prediction using protein-protein associations.
Generates synthetic phase contrast or fluorescence microscope images of bacteria for training deep learning segmentation models.
A Julia toolkit for robust multidimensional profiling of high-content cellular imaging data.
A bioinformatics code kata for practicing DNA-to-protein sequence transformation through test-driven development.
A deep learning model that predicts drug response by fusing multi-omics data with graph convolutional networks.
An ImageJ plugin that converts segmented images into Spatial SBML models for spatial biological simulations.
A web application for generating small ligand conformers for molecular docking using RDKit.
A GNN-based deep learning model that performs drug-specific gene selection for improved drug response prediction.
A PyTorch library providing datasets, transformations, and pretrained models for biological cellular systems.
A PyTorch library providing datasets, transformations, and pretrained models for biological cellular systems.
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