Ana Carolina Leote

The paper introduces CellMAPP and CHART to analyze multiplexed antibody imaging data, revealing modular morphological programs in response to genetic perturbations.

SpatialAgent integrates large language models with dynamic tool retrieval, multimodal interpretation, and claim verification to automate end-to-end spatial biology workflows from gene-panel design to tissue annotation and hypothesis generation.

This paper trains single-cell RNA-seq-based aging clocks to predict mouse age across tissues and cell types, achieving over 90% accuracy in independent tests.

The paper introduces a network-based method for dropout imputation in scRNA-seq data, showing that different genes benefit from different imputation strategies and introducing the ADImpute R-package.