Single-cell analysis in Python. Scales to >100M cells.
- machine-learning
- data-science
- visualize-data
- transcriptomics
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Single-cell analysis in Python. Scales to >100M cells.
Reverse engineering SARS-CoV-2
Deep probabilistic analysis of single-cell and spatial omics data
Implementation of Alphafold 3 from Google Deepmind in Pytorch
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
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
Spatial Single Cell Analysis in Python
A dependency-free cross-platform swiss army knife for PDB files.
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.
LLM for Drug Editing, ICLR 2024
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
Official implementation of JAMIE, Joint variational Autoencoders for Multimodal Imputation and Embedding