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 git repository for Biopython (originally converted from CVS)
Biological foundation modeling from molecular to genome scale
Foundation Models for Genomics & Transcriptomics
:christmas_tree:Visualization and annotation of phylogenetic trees
Python package for graph neural networks in chemistry and biology
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
A Go package for engineering organisms.
Official repository for the ProteinGym benchmarks
A dependency-free cross-platform swiss army knife for PDB files.
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
Schema and generated objects for biolink data model and upper ontology
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome
Genomic sequence storage, indexing and alignment inside PostgreSQL: https://bioseqdb.com/
PhyloNetworks: a julia package with utilities for phylogenetic networks
🏃 The go-to single-cell Foundation Model
Python package for image-based profiling
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations