Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
- diffusion-models
- docking
- binding
- computational-biology
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Brian is a free, open source simulator for spiking neural networks.
- python
- neuroscience
- science
- differential-equations
Computational framework for reinforcement learning in traffic control
- reinforcement-learning
- traffic-control
- benchmark
- autonomous
Segment Anything for Microscopy
- microscopy-images
- segment-anything
- segmentation
- cell-segmentation
Curated list of open-access/open-source/off-the-shelf resources and tools developed with a particular focus on German
- nlp
- corpus-linguistics
- german-language
- computational-linguistics
Tools for computational pathology
- machine-learning
- digital-pathology
- computational-pathology
- biomedical-image-processing
Exascale multiphase flow solver — 2025 Gordon Bell Prize Finalist | 200T grid points on 43K+ GPUs
- gpu
- exascale
- cfd
- fortran
Fusing Histology and Genomics via Deep Learning - IEEE TMI
- pathomic
- fusion
- multimodal
- pathology
A curated list of NLP resources for Hungarian
- nlp
- natural-language-processing
- text-mining
- information-retrieval
⚡ Open-source software for deep learning-based digital pathology
- deep-learning
- machine-learning
- digital-pathology
- computational-pathology
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
- computational-biology
- bioinformatics
- graph-convolution
- deep-learning
MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters filtering, CLI inference, and benchmarks.
- alphafold3
- docking
- drug-design
- drug-discovery
Ruby based API for the project Wortschatz Leipzig.
- rubynlp
- ruby
- nlp
- natural-language-processing
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
- art-history
- color-analysis
- color-extraction
- color-palette