Skip to main content

Wilson, Matthew

Professor of Animal Sciences

Matthew E. Wilson is a native of Indiana and received his B.S. degree in Animal Science from Purdue University in 1994. A work-study position in Dr. Diekman’s laboratory in Animal Sciences was stimulation enough for him to change his focus from pursuing a graduate degree in chemistry to animal science. He accepted a graduate assistantship at Iowa State University under the mentorship of Dr Stephen P. Ford where he earned the M.S. in Physiology of Reproduction in 1996 and the Ph.D. degree in Physiology of Reproduction with a minor in Genetics in 1999. The focus of his graduate research was on placental efficiency, embryo development and litter size in swine. Dr. Wilson accepted a Post-Doctoral Research Fellow position at West Virginia University in 2000 and in 2002, he accepted a position of Assistant Professor in the Division of Animal and Veterinary Sciences at West Virginia University. Dr. Wilson was promoted to the rank of Associate Professor with tenure in 2008 and promoted to Full Professor in 2013. Dr. Wilson has authored or co-authored three book chapters, 5 conference proceedings, more than 70 refereed journal articles, 11 technical publications and more than 80 abstracts. Dr. Wilson has been continuously funded externally since 2007. In recent years he has served as the Director of the WVU Alliance for Regenerative Livestock developing predictive algorithms to determine dry matter intake using machine learning, studying feed and water use efficiency and the impact of grazing on soil health and on farm renewable energy production. He also is involved in work to train service dogs for U.S. military veterans in need, helps train U.S. Army Special Forces Medics in animal agriculture and has a developing focus on agricultural development internationally.


  1. Parenti, L., B. J. Meade, C. Byrd and M. E. Wilson. 2022. The effect of dogs on veteran stress and the impact of veteran and service dog personality characteristics. Anthrozoos (Submitted). 
  2. Blake, N., M. Walker, I. Holaskova, D. J. Mata-Padrino, J. Hubbart, J. Hatton and M. E. Wilson. 2022. Predicting Dry Matter Intake in Beef Cattle. Journal of Animal Science (In preparation). 
  3. Hubbart, J., N. Blake, I. Holásková, D. Mata Padrino, M. Walker and M. E. Wilson. 2022. Challenges in Sustainable Beef Cattle Production: A Subset of Needed Advancements. Challenges (Submitted 9/19/22)
  4. Taiwo, G. , M. D. Idowu, M. E. Wilson, A. Pech-Cervantes, Z. M. Estrada-Reyes, I. M. Ogunade. 2022. Residual Feed Intake in Beef Cattle Is Associated With Differences in Hepatic mRNA Expression of Fatty Acid, Amino Acid, and Mitochondrial Energy Metabolism Genes. Frontiers in Animal Science. 3:1-8.
  5. Taiwo, G., M. Idowu, S. Collins, T. Sidney, M. Wilson, I. Ogunade, A. Pech-Cervantes. 2022. Chemical group-based metabolome analysis identifies candidate plasma biomarkers associated with residual feed intake in beef steers. Frontiers in Animal Science. 2:1-12.
  6. Yost, J. K., J. W. Yates, B. Smith, D. J. Workman, D. Matlick, M. E. Wilson and A. M. Wilson. 2021. Special Forces Medical Sergeant/Special Operations Independent Duty Corpsman Candidates: Large Animal Module. Journal of Special Operations Medicine 21 :115-118.
  7. Yost, J. K., J. W. Yates, M. P. Davis and M. E. Wilson. 2020. The Stockman’s Scorecard: quantitative evaluation of beef cattle stockmanship. Translational Animal Science. 4:1-9.
  8. Yost, J. K., J. W. Yates, D. J. Workman and M. E. Wilson. 2020. The Stockman's Scorecard: validity and reliability as an instrument to measure stockmanship. Journal of Extension 58:1-5.
  9. Yost, J. K., J. W. Yates, B. Smith, D. J. Workman, D. Matlick, M. E. Wilson and A. M.  Wilson.  2019.  Special Forces Medical Sergeant/Special Operations Independent Duty Corpsman Candidates: Large Animal Module.  Journal of Special Operations Medicine (Submitted). 
  10.  Krombeen, S. K., V. Shankar, R. E. Noorai, C. A. Saski, J. L. Sharp, M. E. Wilson, T. A. Wilmoth. 2019. The identification of differentially expressed genes between extremes of placental efficiency in maternal line gilts on day 95 of gestation. BMC Genomics 20:254-269.
  11. Krombeen, S. K., W. C. Bridges, M. E. Wilson and T. A. Wilmoth. 2018. Factors contributing to the variation in placental efficiency on days 70, 90, and 110 of gestation in gilts. Journal of Animal Science 97:359-373.
Download CV