Computational Biology
Showing 18 of 90 projects
A machine learning pipeline that predicts 70 cell health phenotypes from Cell Painting image-based morphology profiles.
An MCP server that enables natural language conversation for analyzing spatial transcriptomics data through 60+ curated methods.
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.
Generates synthetic phase contrast or fluorescence microscope images of bacteria for training deep learning segmentation models.
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.
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 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.
A GNN-based deep learning model that performs drug-specific gene selection for improved drug response prediction.
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