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TranslatedA knowledge graph for mathematics (primary school to high school), English (grade 3 to high school), and junior high school physics: 1,644 knowledge points, 2,403 prerequisite edges, and 6,723 questions, aligned with the curriculum standards, with an adaptive prerequisite diagnostic.
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Graphormer is a general-purpose deep learning backbone for molecular modeling.
A python module for scientific analysis of 3D data based on VTK and Numpy
Spectral simulation of analog photography processes
3D medical imaging reconstruction software
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)
A Euclidean diffusion model for structure-based drug design.
Graph-linked unified embedding for single-cell multi-omics data integration
GraphDTA: Predicting drug-target binding affinity with graph neural networks
Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".
Schema and generated objects for biolink data model and upper ontology
Medical LLM agent and MRI segmentation workspace built on PharmaLLM, with LangGraph, vLLM, and BEU-Net.
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
Learning cell communication from spatial graphs of cells
TypeDB Bio: Biomedical Knowledge Graph
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions