Bioinformatics
Showing 23 of 203 projects
A Julia toolkit for robust multidimensional profiling of high-content cellular imaging data.
Zsh shell completion scripts for bioinformatics command-line tools to enhance productivity.
A MATLAB-based deep learning platform for automated cell division tracking and replicative lifespan analysis from microscopy image sequences.
An Igor Pro package for analyzing 2D cell migration data from manual tracking in ImageJ/FIJI.
A deep learning model that predicts drug response by fusing multi-omics data with graph convolutional networks.
A bioinformatics code kata for practicing DNA-to-protein sequence transformation through test-driven development.
A Python package for analyzing high-throughput single-cell imaging data, including protein abundance, endocytosis, and particle tracking.
A web application for generating small ligand conformers for molecular docking using RDKit.
A MATLAB-based toolbox for interactive visualization and analysis of multiplexed image cytometry data.
A multi-channel neural network for predicting compound-protein interactions using molecular and protein sequence embeddings.
An R package for importing and visualizing bacterial microscopy segmentation and fluorescence data using ggplot2.
Accelerated structure similarity searching for large small molecule datasets using embedding and indexing.
A deep learning model for predicting cancer drug response using data enhancement and edge-collaborative update strategies.
A header-only C++11 library using OpenCV for high-throughput image-based plant phenotyping.
A Python library for analyzing mRNA and protein spatial and temporal distributions in single-cell confocal microscopy images.
A Common Lisp Jupyter widget for molecular visualization using NGL, providing interactive 3D structures in notebooks.
Interactive visualization of higher-order graphs in Python using proportion of degrees by communities.
An Oh-My-Zsh plugin providing functions and aliases to simplify QIIME 2 workflows for microbiome data analysis.
Attention-based GNN model for predicting drug sensitivity and explaining gene contributions using a drug-cell-gene heterogeneous network.
An R package for reading, writing, and visualizing medical imaging data in ANALYZE, NIfTI, and AFNI formats.
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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