Samuel Morabito

MET inhibition exploits conserved regulatory dependencies in malignant rhabdoid tumors

This study identifies MET signaling as a targetable vulnerability in rhabdoid tumors through integrated single-cell multi-omic and spatial transcriptomics analyses.

An Integrated Single-Nucleus Atlas Resolves Cell-Type-Specific Programs and Molecular Subtypes in Alzheimer's Disease

The paper constructs a single-nucleus transcriptomic atlas of Alzheimer's disease and identifies cell-type-specific molecular subtypes and therapeutic targets using a new framework.

Dysregulation of transcription networks regulating oligodendrogenesis in age-related decline in CNS remyelination

The paper identifies age-related dysregulation of transcription networks in oligodendrocyte differentiation using single-nucleus RNA and ATAC sequencing in mice, with parallels in MS lesions.

Single-nucleus multi-omics identifies shared and distinct pathways in Pick's and Alzheimer's disease

This study uses single-nucleus multi-omics to identify shared and distinct regulatory pathways in Pick's and Alzheimer's disease, revealing disease-specific enhancers and TF binding patterns.

Decoding the immune response in leptomeningeal disease through single-cell sequencing of cerebrospinal fluid

The paper uses single-cell sequencing and spatial transcriptomics to compare immune responses in leptomeningeal disease with other CNS disorders, identifying disease-specific immune environments and progression mechanisms.

Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer's Disease

This study uses spatial transcriptomics and single-nucleus RNA-seq to compare genetic and sporadic Alzheimer's Disease, finding similar spatial and cell-type specific changes between sporadic AD and AD in Down Syndrome.

The ENCODE mouse postnatal developmental time course identifies regulatory programs of cell types and cell states

The paper identifies regulatory programs in postnatal mouse development using single-nucleus data, revealing cell-type-specific and common regulatory topics across multiple tissues.

High dimensional co-expression networks enable discovery of transcriptomic drivers in complex biological systems

This paper introduces hdWGCNA, a framework for analyzing co-expression networks in high-dimensional transcriptomics data, demonstrating its application in identifying disease-relevant modules in single-cell datasets.

The ENCODE4 long-read RNA-seq collection reveals distinct classes of transcript structure diversity

Long-read sequencing of 81 human and mouse samples yields 200,000 full-length transcripts plus a triplet framework that separates promoter choice, splicing and 3' end use across tissues.

Single-soma transcriptomics of tangle-bearing neurons in Alzheimer's disease reveals the signatures of tau-associated synaptic dysfunction

The paper identifies gene expression signatures in Alzheimer's disease neurons with tau aggregates, revealing shared and subtype-specific molecular changes related to synaptic function and metabolism.

Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer’s disease

This study identifies conserved transcriptomic networks in Alzheimer’s disease by integrating multi-omics data across multiple cohorts and cell types.

Integrated single-cell potency and expression landscape in mammary epithelium reveals novel bipotent-like cells associated with breast cancer risk

The paper introduces LandSCENT, a computational method to identify bipotent-like cells in mammary epithelium, which are associated with breast cancer risk.