Matthew D. Wilkerson, Ph.D.

Matthew D. Wilkerson, Ph.D.

Matt Wilkerson

Name: Matthew D. Wilkerson, Ph.D.

Department of Primary Appointment: Anatomy, Physiology & Genetics
Position: USU Faculty
Title: Director, Informatics Core (CHIRP), Adjunct Associate Professor

Affiliated Center: CHIRP

Lab Website


The Bioinformatics Core provides computational biology analysis and infrastructure for CHIRP genomic research studies. Our mission is to discover and characterize genomic alterations in patient specimens in order to enable precision medicine, such as characterizing the molecular etiology of disease, predicting disease risk and outcome, and discovering molecular subtypes of disease. We apply and develop computational methods for analyzing high throughput sequencing from the CHIRP sequencing core or from CHIRP affiliated investigators. Bioinformatics Core analysis spans low level analysis to biological hypothesis evaluation and exploration.

The CHIRP Bioinformatics Core is under the direction of Dr. Matthew D. Wilkerson (PubMed). Dr. Wilkerson’s prior academic research has resulted in the discovery of expression subtypes based upon genomewide expression profiles of various cancer types, such as lung adenocarcinoma, lung squamous cell carcinoma, and pheochromocytoma/paraganglioma among others (e.g., Fig 5A). He has published integrated genomic studies that characterized these novel expression subtypes with differential molecular pathogenesis (somatic mutations, germline mutations, copy number alterations, epigenetic alterations), differential patient profiles and environmental exposures, and differential patient survival and chemotherapy response of these molecular subtypes – thus establishing that these expression subtypes are an important classification for precision medicine. In addition, Dr. Wilkerson has developed original computational methods, including methods for identifying somatic mutations in patient-matched DNA and RNA sequencing, for genomic subtype discovery, and for structural comparative genomics. These methods also enable precision medicine, such as identifying actionable mutations in low purity tumors, which has important implications for targeted cancer therapy (e.g. Fig 5).

Schedule a Bioinformatics Core Consultation.