Rate My Professor Travis Wheeler

Travis Wheeler is an Associate Professor in the Department of Pharmacy Practice and Science at the University of Arizona, with additional appointments as Associate Professor in the Genetics Graduate Interdisciplinary Program, Applied Mathematics Graduate Interdisciplinary Program, and the BIO5 Institute. He received a B.A. in Ecology and Evolutionary Biology from the University of Arizona in 1995 (cum laude, Phi Beta Kappa, minors in Anthropology and English), an M.S. in Computer Science in 2006, and a Ph.D. in Computer Science in 2009 from the same institution, with advisors John Kececioglu and Mike Sanderson and a minor in Evolutionary Biology. After his doctorate, Wheeler served as Postdoctoral Associate (2009-2011) and Senior Research Scientist (2011-2014) in Sean Eddy's group at the HHMI Janelia Research Campus. He then joined the University of Montana's Department of Computer Science as Assistant Professor from 2014 to 2019 and Associate Professor from 2019 to 2022. Earlier roles include Lead Architect and Developer for the Tree of Life Web Project at the University of Arizona (2000-2003) and software development at Intuit, Inc. (1995-2000). In 2022, he returned to the University of Arizona in his current position.

With over 25 years of experience, Wheeler develops algorithms, statistical models, machine learning methods, and software for biological data problems, spanning statistical modeling of sequence families, text indexing, low-level optimization, deep neural networks, natural language processing, genomic and proteomic analysis, computational drug discovery, mass spectrometry data analysis, and automated animal tracking and behavior classification. Key publications include "Nhmmer: DNA homology search with profile HMMs" (Bioinformatics, 2013), "Dfam: A database of repetitive DNA based on profile hidden Markov models" (Nucleic Acids Research, 2013), "Skylign: A tool for creating informative, interactive logos representing sequence alignments and profile hidden Markov models" (BMC Bioinformatics, 2014), "An optimized FM-index library for nucleotide and amino acid search" (Algorithms for Molecular Biology, 2021), "NEAR: Neural embeddings for amino acid relationships" (Bioinformatics, 2025), and "Simpatico: accurate and ultra-fast virtual drug screening with atomic embeddings" (bioRxiv, 2025). His work advances sequence alignment, database search, annotation, and applications in genomics, drug discovery, and beyond.