Ana-Maria Istrate

The paper introduces TranscriptFormer, a generative model trained on 112 million cells across 12 species, demonstrating cross-species cell type classification and disease state prediction.

This paper introduces rbio1, a biology reasoning model trained using soft verification via biological world models, achieving state-of-the-art performance on perturbation prediction.

CZ CELLxGENE Discover provides a platform for scalable exploration and analysis of aggregated single-cell transcriptomic data across multiple studies.

The paper shows that combining language-based gene representations with experimental data improves perturbation prediction in single-cell data.