Daniel Feliciano

This paper introduces sOrganellomics, a method to map cell state diversity and metabolic adaptation in tissues using spatial imaging and machine learning, revealing new insights into hepatocyte organization and metabolic changes under stress.

This study uses cell-cell fusion to investigate how mitotic and interphase nuclei interact in shared cytoplasm, revealing checkpoint override events and plasticity in cell cycle control.

This paper introduces STORM, a statistical framework for analyzing spatial patterns in multi-omics data, demonstrating reliable performance in detecting spatial structures and supporting study design decisions.

The paper develops and validates a genetically encoded fluorescent sensor, iG6PSnFR, for measuring glucose-6-phosphate dynamics across multiple biological contexts.

This paper develops an improved FBP sensor, HYlight2, for in vivo imaging of glycolysis in various organisms.

Imaging of mitochondria and lipid droplets (LDs) across mouse liver lobules shows fasting, not Western diet, expands mitochondria-LD contacts; PLIN5 phosphomutants tune contacts and lipid storage.

This study shows Imp1 regulates temporal fate transitions in radial glia during cortical development, affecting neuronal identity and spatial organization through dosage and stage-dependent mechanisms.

MicroSplit uses deep learning to computationally unmix fluorescent microscopy data, enabling faster imaging and reduced photon exposure by separating multiple cellular structures from a single channel.

TEMPO enables sequential genetic labeling and manipulation of vertebrate cell lineages to study birth-order-dependent cell fates.