Python Toolkit for Causal and Probabilistic Reasoning
- python
- bayesian-networks
- causal-inference
- causal-discovery
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Python Toolkit for Causal and Probabilistic Reasoning
Cartopy - a cartographic python library with matplotlib support
Python interface for igraph
Python package for graph neural networks in chemistry and biology
In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry
Interactive network visualization in Python and Dash, powered by Cytoscape.js
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)
Graph-linked unified embedding for single-cell multi-omics data integration
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data
FOREST is a research agent for long-horizon science, where evidence gets lost, errors compound, and goals drift. It explores ideas, reads literature, forms hypotheses, runs real experiments, analyzes results, revises paths, and builds a full paper—all in an editable graph you can inspect, branch, redirect, with claims and figures linked to evidence
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
TypeDB Bio: Biomedical Knowledge Graph
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
Cryptographic Dataset Generation & Modelling Framework
💬 Trace citation chains for any concept across research papers and render them as an interactive graph.
Python Frontend to Algorithms of the Algorithm Engineering Group Heidelberg
Nova DSO Tracker is an open-source Flask application for astrophotographers, providing real-time tracking of deep-sky objects' altitude, observability prediction, and integration with Stellarium and SIMBAD databases.
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