Andrew Doxey is a bioinformatician with research interests in biological data mining, protein function prediction, and comparative and evolutionary genomics.
The Doxey Lab develops computational methods to predict novel molecular or systems-level functions from genomes and other “omics” datasets. Current efforts are focused largely on uncharacterized proteins from newly sequenced microbial genomes and metagenomes.
The Doxey Lab combines both “dry” (computational) and “wet” (biochemical/molecular) approaches, and works closely with a diverse range of local and international collaborators.
- Computational Biology
- Molecular Genetics
Due to continual advances in sequencing and other “omics” technologies, biology is experiencing a big data revolution. Computational methods are required not only to interpret newly sequenced genomes, but search through a vast quantity of existing biological information to reveal previously uncharacterized functionality.
The Doxey lab is interested in both the development and application of computational methods to predict novel molecular functions (protein-coding and non-coding) from genomic, structural, and other high-throughput datasets. We explore three separate but overlapping areas:
Predicting novel protein families and functions: We develop methods that combine sequence analysis with structural bioinformatics to predict and experimentally validate protein functions of interest. Currently, we are focusing efforts on predicting new families and functions of bacterial flagellins, clostridial toxins, and proteolytic enzymes.
Predicting evolutionary adaptations in genes and genomes: We combine sequence analysis, phylogenetics and structural modeling to pinpoint adaptive events in genes and genomes. We are interested in inferring mechanisms of neofunctionalization and functional divergence in protein families as well as non-coding regulatory elements.
Comparative functional metagenomics: The Doxey Lab is also developing computational approaches to functionally annotate metagenomes and detect biologically relevant differences between them. Recent work includes the development of the MetAnnotate framework for combined taxonomic and functional profiling of metagenomic datasets.
* Professor Doxey actively seeks eager and talented graduate or undergraduate students interested in bioinformatics, genomics, or molecular biology.
Professor Doxey teaches both undergraduate and graduate courses. Course offerings have included
- BIOL 266 Introduction to Computational Biology
- BIOL 469 Genomics
- BIOL 349 Synthetic Biology
- BIOL 614 Bioinformatics Tools and Techniques
Please see the Doxey Lab website for a current list of his peer-reviewed articles.
Awards and Distinctions
- 2017 Outstanding Performance Award
- 2010-2012 NSERC Postdoctoral Fellowship (PDF)
- 2010 Governor General’s Gold Medal for top Ph.D., University of Waterloo
- 2010 W.B. Pearson Medal for Creative Doctoral Research, University of Waterloo
University of Waterloo Affiliations
- Centre for Bioengineering and Biotechnology
- Waterloo Centre for Microbial Research (member)
Professional Associations and Service
- International Society for Computational Biology
- American Association for the Advancement of Science
2010 PhD Bioinformatics, University of Waterloo
2005 BSc Biology, University of Waterloo