Fani Memi

TERRA is a foundation model for spatial transcriptomics that predicts tissue behavior under perturbation and identifies multi-scale biological insights across tissues.

The paper provides a high-resolution molecular and cellular analysis of Broca's area and motor cortex across developmental stages, identifying distinct cellular signatures and vulnerabilities to neurodevelopmental disorders.

The paper benchmarks dopaminergic stem cell models and cell therapy candidates using a human brain atlas to identify off-target populations and lineage plasticity.

The paper presents a spatial transcriptomic atlas of autism-associated genes in the developing human brain, identifying convergence in the thalamus and germinal zones.

The paper identifies a spatiotemporal cancer cell trajectory in glioblastoma that explains tumor heterogeneity across regions and subclones.

This study uses single-cell multiomics to identify regulatory programs and plasticity regulators in glioblastoma, revealing MYT1L as a key repressor of malignant plasticity.

This study constructs a multiomic atlas of human early skeletal development using single-nuclei transcriptomics, epigenomics, and spatial transcriptomics to uncover regulatory mechanisms and cell states involved in bone and joint formation.

The paper introduces NicheCompass, a graph deep learning method for characterizing cell niches in spatial omics data, showing improved performance in identifying and analyzing niches across multiple biological contexts.

The paper introduces cell2fate, a model-based RNA velocity method that improves cell fate prediction by decomposing velocity solutions into modules and applying it to human brain development data.