Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
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Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Official repository for the Boltz biomolecular interaction models
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
Code for running RFdiffusion
Single-cell analysis in Python. Scales to >100M cells.
Reverse engineering SARS-CoV-2
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
This package contains deep learning models and related scripts for RoseTTAFold
Data intensive science for everyone.
Deep probabilistic analysis of single-cell and spatial omics data
Biological foundation modeling from molecular to genome scale
Cloud-native genomic dataframes and batch computing
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis
Python package for graph neural networks in chemistry and biology
In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
Official release of the ProGen models
Spatial Single Cell Analysis in Python
Generative biopolymer design with rich conditioning.
A tool for semi-automatic cell type classification
RNA Velocity generalized through dynamical modeling
Graph-linked unified embedding for single-cell multi-omics data integration
A dependency-free cross-platform swiss army knife for PDB files.