Bradley T. Martin Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
faculty
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Biography and Research Information
OverviewAI-generated summary
Bradley T. Martin's research focuses on the application of genomic and computational methods to understand biodiversity, species delimitation, and conservation. He has investigated the use of machine learning for species delimitation in North American box turtles (Terrapene spp.) and developed tools such as ClineHelpR for genomic cline outlier detection. His work also addresses taxonomic uncertainty, as seen in his phylogenomic analysis of the Gila robusta complex in the Colorado River. Martin has explored the role of biological structures, such as dead razor clam (Pinna bicolor) graveyards, as drivers of epibenthic biodiversity through manipulative experiments. He has also developed GeoGenIE, a deep learning approach to predict the geographic provenance of biodiversity samples from genomic single-nucleotide polymorphisms (SNPs). His research has been supported by funding and has resulted in 29 publications with 270 citations, and an h-index of 9. He has collaborated extensively with researchers at the University of Arkansas at Fayetteville, including Michael E. Douglas, Marlis R. Douglas, and Tyler K. Chafin.
Metrics
- h-index: 9
- Publications: 29
- Citations: 273
Selected Publications
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Historic and contemporary selection define conservation units for a short-range endemic within an anthropogenically-altered riverscape (2025)
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GeoGenIE: a deep learning approach to predict geographic provenance of biodiversity samples from genomic SNPs (2024)
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Relictual Hybridization and Biogeography of Massasauga Rattlesnakes ( <i>Sistrurus</i> spp.) (2022)
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ClineHelpR: an R package for genomic cline outlier detection and visualization (2021)
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Taxonomic Uncertainty and the Anomaly Zone: Phylogenomics Disentangle a Rapid Radiation to Resolve Contentious Species ( <i>Gila robusta</i> Complex) in the Colorado River (2021)
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The choices we make and the impacts they have: Machine learning and species delimitation in North American box turtles ( <i>Terrapene</i> spp.) (2021)
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