Papers

FourierDrug: a domain generalization framework for robust drug response prediction via frequency-space asymmetric attention.

Causal effect estimation from trans-regulatory single-cell CRISPR screens.

Illuminating cell states by a comprehensive and interpretable single cell foundation model.

rbio1 - training scientific reasoning LLMs with biological world models as soft verifiers

Predicting cellular responses to perturbation across diverse contexts with State

Virtual Cell Challenge: Toward a Turing test for the virtual cell.

Scaling Large Language Models for Next-Generation Single-Cell Analysis

Scupa: single-cell unified polarization assessment of immune cells using the single-cell foundation model.

CZ CELLxGENE Discover: a single-cell data platform for scalable exploration, analysis and modeling of aggregated data.

A cell atlas foundation model for scalable search of similar human cells.

Large-scale foundation model on single-cell transcriptomics.

scGPT: toward building a foundation model for single-cell multi-omics using generative AI.

Universal Cell Embeddings: A Foundation Model for Cell Biology

Predicting transcriptional outcomes of novel multigene perturbations with GEARS.

Transfer learning enables predictions in network biology.

Predicting cellular responses to complex perturbations in high-throughput screens.

Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq.

The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans.

scGen predicts single-cell perturbation responses.

Deep generative modeling for single-cell transcriptomics.