Matt Jensen

The paper analyzes bulk RNA-seq data from brain tumors and healthy samples to identify differential regulation of synaptic components and their impact on tumor progression and patient survival.

This paper constructs a unified transcriptional landscape of breast cancer using bulk RNA-seq data from multiple cohorts, identifying subtype and microenvironmental programs associated with therapeutic resistance.

The paper constructs a unified transcriptomic landscape of lung cancer using RNA-seq data from 1,824 tumors, identifying nine molecular clusters with distinct biological and clinical features.

The paper constructs a transcriptomic landscape for medulloblastoma and ependymoma, revealing subtype-specific biology through clustering and molecular signatures.

This study combines bulk RNA-Seq datasets to create a transcriptomic landscape of meningiomas, identifies subtypes with distinct biology and prognosis, and provides an interactive tool for outcome prediction.

The paper combines five RNA-seq datasets to create a reference landscape of human brain tissues and tumors, enabling comparative gene expression analysis across normal and neoplastic samples.