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
This package contains deep learning models and related scripts for RoseTTAFold
Python package for graph neural networks in chemistry and biology
A Go package for engineering organisms.
R package for detecting doublets in single-cell RNA sequencing data
A Python Package for Protein Dynamics Analysis
SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.
Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk
talk with NCBI entrez using R
A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.
PhyloNetworks: a julia package with utilities for phylogenetic networks
LLM for Drug Editing, ICLR 2024
Data visualisation web components for the life sciences.
Python package for image-based profiling
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
A tool for cell instance aware segmentation in densely packed 3D volumetric images
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
Python package for analysis of multiomic single cell RNA-seq and ATAC-seq.