Ana Lucia Mora

SpaFlow models ligand-receptor interactions in spatial transcriptomics data by simulating diffusion and binding processes, revealing spatially coherent signaling patterns in multiple disease contexts.

The paper integrates single-cell RNA sequencing and spatial transcriptomics to identify CTHRC1+ fibroblasts as key fibrogenic cells in IPF, showing how culture affects their transcriptional profile.

This paper introduces DeepSAS, a deep graph framework to identify senescent cells and their associated genes, revealing cell-type-specific senescence features in aging and disease.

The paper develops SenSet, a gene signature for human lung senescence, validated in 3D culture models and identifies cell-type specific senescence mechanisms in aging and disease.

The paper develops scDOT, a method combining spatial transcriptomics and single-cell RNA-seq with optimal transport to improve spatial mapping of senescent cells and identify novel genes involved in cell-cell interactions.

This study uses MALDI-MSI to analyze lipids and proteins in human lung fibroblasts, revealing senescence-related changes at the single-cell level.

scResolve recovers single-cell expression profiles from multi-cellular spatial transcriptomics data, enabling cell type-specific analysis and rare population detection in human tissues.

The paper identifies LEF1 isoforms as key regulators of cellular senescence and aging through transcriptomic analysis and validation in human and mouse models.

The paper identifies early fibroblast transitions to a profibrotic state in IPF using scRNA-seq and validates MOXD1 as an early marker.

The paper uses spatial transcriptomics and the MAPLE algorithm to analyze fibrotic lung tissue, identifying spatial biomarkers and fibrotic programs in IPF.

This study shows TSC2 deficiency in pulmonary vascular smooth muscle cells leads to ECM remodeling, hyper-proliferation, and pulmonary hypertension, which can be reversed by restoring TSC2 function.