Matthew Scotch, MPH
Research & Publications
Biography
Research Summary
Matthew Scotch is Associate Professor of Biomedical Informatics in the College of Health Solutions and Assistant Director of the Biodesign Center for Environmental Health Engineering at Arizona State University. His research focuses on the theory and application of phylogeography to study the migration of zoonotic RNA viruses with a particular interest in influenza A viruses. Work in his lab includes the integration, analysis, and presentation of viral genetics for public health/animal health surveillance.
Current projects include studying approaches to advance phylogeography models in order to identify climate, population, and genetic factors that support viral spread (funding: NIH/NLM R01LM012080) and geospatial metadata in virus sequence databases and approaches to include observation error for virus phylogeography (funding: NIH/NIAID R01AI117011).
His lab group is also interested in the molecular epidemiology of zoonotic viruses including the amplification and sequencing of influenza A genes for studying spread among avian and human hosts.
Extensive Research Description
- Bioinformatics for Public Health (systems that leverage molecular sequence data to support decision-making at health agencies)
- Zoonotic disease surveillance (linking health data on animal and humans)
- Phylogeography of zoonotic RNA viruses
- Molecular epidemiology of zoonotic RNA viruses
- Sequencing and analysis of the Influenza A genome
- Geographical Information Systems (GIS)
- Natural Language Processing (NLP)
Research Image
ZooPhy Lab
Selected Publications
- The Effects of Sampling Location and Predictor Point Estimate Certainty on Posterior Support in Bayesian Phylogeographic Generalized Linear Models.Magee D, Taylor JE, Scotch M. The Effects of Sampling Location and Predictor Point Estimate Certainty on Posterior Support in Bayesian Phylogeographic Generalized Linear Models. Scientific Reports 2018, 8:5905.
- GeoBoost: accelerating research involving the geospatial metadata of virus GenBank records.Tahsin T, Weissenbacher D, O'Connor K, Magge A, Scotch M, Gonzalez-Hernandez G. GeoBoost: accelerating research involving the geospatial metadata of virus GenBank records. Bioinformatics (Oxford, England) 2018, 34:1606-1608.
- Deep neural networks and distant supervision for geographic location mention extraction.Magge A, Weissenbacher D, Sarker A, Scotch M, Gonzalez-Hernandez G. Deep neural networks and distant supervision for geographic location mention extraction. Bioinformatics (Oxford, England) 2018, 34:i565-i573.
- Phylogeography of H5N1 avian influenza virus in Indonesia.Njoto EN, Scotch M, Bui CM, Adam DC, Chughtai AA, MacIntyre CR. Phylogeography of H5N1 avian influenza virus in Indonesia. Transboundary And Emerging Diseases 2018, 65:1339-1347.
- The effects of random taxa sampling schemes in Bayesian virus phylogeography.Magee D, Scotch M. The effects of random taxa sampling schemes in Bayesian virus phylogeography. Infection, Genetics And Evolution : Journal Of Molecular Epidemiology And Evolutionary Genetics In Infectious Diseases 2018, 64:225-230.
- Avian influenza virus ecology and evolution through a climatic lens.Morin CW, Stoner-Duncan B, Winker K, Scotch M, Hess JJ, Meschke JS, Ebi KL, Rabinowitz PM. Avian influenza virus ecology and evolution through a climatic lens. Environment International 2018, 119:241-249.
- Bayesian Phylogeography and Pathogenic Characterization of Smallpox Based on HA, ATI, and CrmB Genes.Adam DC, Scotch M, MacIntyre CR. Bayesian Phylogeography and Pathogenic Characterization of Smallpox Based on HA, ATI, and CrmB Genes. Molecular Biology And Evolution 2018, 35:2607-2617.
- Characterising routes of H5N1 and H7N9 spread in China using Bayesian phylogeographical analysis.Bui CM, Adam DC, Njoto E, Scotch M, MacIntyre CR. Characterising routes of H5N1 and H7N9 spread in China using Bayesian phylogeographical analysis. Emerging Microbes & Infections 2018, 7:184.
- Bayesian phylogeography of influenza A/H3N2 for the 2014-15 season in the United States using three frameworks of ancestral state reconstruction.Magee D, Suchard MA, Scotch M. Bayesian phylogeography of influenza A/H3N2 for the 2014-15 season in the United States using three frameworks of ancestral state reconstruction. PLoS Computational Biology 2017, 13:e1005389.
- A high-precision rule-based extraction system for expanding geospatial metadata in GenBank records.Tahsin T, Weissenbacher D, Rivera R, Beard R, Firago M, Wallstrom G, Scotch M, Gonzalez G. A high-precision rule-based extraction system for expanding geospatial metadata in GenBank records. Journal Of The American Medical Informatics Association : JAMIA 2016, 23:934-41.