Julian M.W. Quinn

CRUX is a platform for analyzing cancer genome data, enabling cohort comparisons, biomarker discovery, and visualization with a user-friendly interface and local analysis options.

mity detects low heteroplasmy mitochondrial variants in whole genome sequencing data, improving diagnostic rates for mitochondrial diseases.

The paper maps the osteocyte transcriptome in mice, identifies 1239 genes, and links them to skeletal disease susceptibility in humans.

The paper identifies genes and molecular pathways associated with Alzheimer’s disease by analyzing gene expression data from multiple related conditions and using network-based methods.

The paper identifies differentially expressed genes, pathways, transcription factors, and microRNAs between follicular thyroid carcinoma and follicular thyroid adenoma using system biology approaches.

The paper identifies 12 dysregulated genes shared between brain and blood cells in Parkinson's disease using transcriptomic and eQTL data, validated with dbGaP.

The paper identifies gene expression changes in respiratory tissues exposed to welding fumes and links them to respiratory system diseases through network analysis.

This study identifies blood-based biomarker signatures and candidate drugs for Alzheimer's disease through integrative transcriptomics and network analyses.

The paper identifies common molecular biomarker signatures in blood and brain tissues of Alzheimer's disease patients, revealing shared gene expression patterns and regulatory elements.

The paper identifies differentially expressed genes between welding fumes and five neurodegenerative diseases using network analysis and gene expression data.

This paper identifies 518 genetic loci associated with bone mineral density and fracture risk, validates causal genes in mice, and provides insights for osteoporosis drug development.

The paper identifies dysregulated genes and shared genetic factors in Parkinson's disease using network-based analysis of gene expression data from multiple conditions.

The paper develops a framework to analyze how mitochondrial dysfunction affects neurological disorders by examining gene-disease networks, KEGG pathways, and protein interactions.

The paper identifies gene expression patterns in ovarian cancer associated with disease progression and mortality using clinical and transcriptomic data from TCGA.