Andrew R Moorman

Generative Neuromorphic Programming of Mammalian Cells

This paper introduces a neuromorphic framework for programmable mammalian cells, enabling the design of analog circuits through generative programming and biomorphic neural networks.

Ecological determinants of disease and immunity in myelodysplastic syndromes

This study uses spatial transcriptomics and single-cell analysis to reveal how MDS bone marrow microenvironments are altered, showing TGFβ dysregulation in malignant cells and immune escape mechanisms.

Oncogenic and tumor-suppressive forces converge on a progenitor niche at the benign-to-malignant transition

In mouse pancreatic cancer models, p53, CDKN2A and SMAD4 programs converge on a rare Kras-mutant progenitor-like state whose niche KRAS inhibition collapses and p53 loss expands.

A single-cell atlas of spatial and temporal gene expression in the mouse cranial neural plate

The paper creates a single-cell RNA sequencing atlas of gene expression during mouse cranial neural tube closure, identifying spatially regulated genes and SHH-regulated programs in different brain regions.

Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics data

Segger improves cell segmentation in spatial transcriptomics by using a graph neural network, achieving high sensitivity and speed with minimal manual intervention.

Signaling-based neural networks for cellular computation

The paper models phosphorylation/dephosphorylation cycles as molecular neurons and shows they can function as biomolecular neural networks capable of performing classification tasks.