BRAID is a department within Genentech dedicated to advancing biological and clinical sciences through artificial intelligence. Our core focus is on developing foundation models—general-purpose AI models trained on large-scale biological datasets—which we fine-tune for specialized applications.
At BRAID, we not only develop cutting-edge AI tools but also actively use them to advance scientific discovery. All our tools are made available to the scientific community through the links on this page. We always welcome feedback—feel free to contact Tommaso or the BRAID leadership team with any input or suggestions.
gReLU: Train, interpret, and apply deep learning models to DNA sequences
SCimilarity : Unifying representation of single cell expression profiles
Decima: DNA sequence models on single-cell RNA-seq data
VCI: Estimating individual counterfactual treatment effects
Tangram: Spatial alignment of single cell and spatial transcriptomics
OCTCube: An ophthalmology foundation model for OCT images
BwR: Efficient and expressive graph generative modeling
GraphGUIDE: Interpretable and controllable conditional graph generation
ARGMINN: Mechanistically interpretable neural network for regulatory genomics
SPICE: Uncertainty estimation via conformal prediction for deep learning models
CTRL: RL-based conditional control for diffusion models
MolCap-Arena: Benchmark on language-enhanced molecular property prediction
PaSCient: Multi-cellular representations of single-cell transcriptomics data
Polygraph: Evaluation and comaprison of nucleic acid sequences for regulatory element design
regLM: hyenaDNA-based autoregressive language models on DNA for generation of novel regulatory elements
CellArr: TileDB-backed store for large collections of genomic experimental data
MiloDE: Sensitive DE testing using cell neighborhoods
Cumulus: A series of Cloud-based scalable and efficient single-cell genomics data analysis workflows
Pegasus: A scalable and efficient tool for analyzing transcriptomes of millions of single cells
Cirrocumulus: An interactive visualization tool for large-scale single-cell genomics data
Harmony-PyTorch: An efficient PyTorch implementation of Harmony algorithm, used for data integration and batch correction
NMF-Torch: An efficient PyTorch implementation of Non-negative Matrix Factorization (NMF) and integrative NMF (iNMF) algorithms, used for gene program analysis and batch correction
