Official git repository for Biopython (originally converted from CVS)
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- bioinformatics
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Official git repository for Biopython (originally converted from CVS)
Official repository for the Boltz biomolecular interaction models
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
A Go package for engineering organisms.
Generative biopolymer design with rich conditioning.
Official repository for the ProteinGym benchmarks
A Practical and Efficient NCBI Taxonomy Toolkit, also supports creating NCBI-style taxdump files for custom taxonomies like GTDB/ICTV
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
Repository for Nicheformer: a foundation model for single-cell and spatial omics
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
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
Data visualisation web components for the life sciences.
Accurate and efficient spot detection for microscopy data
Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
Toolbox for the analysis of smFISH images.
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
Tool for precise, interactive, fast and scalable FISH spot detection
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.
Interpretable modeling of cellular responses to drug perturbations using cycle consistence learning
DeepAEG: A model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.