Alexander Pelletier is an M.Sc. student at the University of Ottawa in Biochemistry with a specialization in Bioinformatics. He is under the supervision of Prof. Mathieu Lavallée-Adam and Prof. Daniel Figeys. He completed his undergraduate degree in Bioengineering: Bioinformatics at the University of California, San Diego in 2017.
Research Interests
Alexander specializes in the development of machine learning algorithms to analyze and process large proteomics datasets and has a strong background in both computer science and biochemistry. Previously, he developed a machine learning tool which uses Bayesian inference to identify proteins bound by a compound via fractionation-based proteomics. He has experience in improving the efficiency and usability of existing proteomics software and has a working knowledge of common genomics and proteomics software tools.
Alexander is currently applying his knowledge of proteomics and bioinformatics to improve the detection of low abundance bacterial species of the human gut microbiome. Metaproteomics has emerged as a state-of-the-art technology for identifying thousands of bacterial proteins in a microbiome sample via mass spectrometry. However, the proteins identified are predominantly from bacterial species with high abundance, with few to none identified from low abundance bacterial species. The identification of these low abundance bacterial species is vital for a complete understanding of the human gut microbiome’s biological function. Alexander aims to create a machine learning algorithm which will increase the mass spectrometer’s identification sensitivity of lower abundant bacterial species in the human gut microbiome.
Program Goals
- Cultivate a strong understanding of multiple systems-biology technologies
- Expand knowledge of machine learning algorithms to solve complex biological problems
- Establish effective communication, networking, and project management skills