Our People

Haiyang Chang

Program: M.Sc.

Advisor: Dr. Stefan Keller

Co-advisor: Dr. Dan Ashlock

 

Research:

The adaptive immune response plays a key role in recognizing pathogens and determines health and disease in vertebrates. The protection mechanism of adaptive response is mediated by the antigen receptors (ARs) on the surface of lymphocytes. Specifically, an individual’s AR repertoire helps understand, diagnose and treat diseases. The data are from previously collected Canine immune repertoire sequencing data under normal and pathological conditions. The data analysis for this research will be confined to clustering of AR sequences (clonotypes) and a network map that displays the functional association of clonotypes within a given data set will be constructed. Finally we hope a database that integrates sequencing data from various projects based on variables such as species, disease, tissue, etc.. would be created.

Thanuja Fernando

Thanuja Fernando

Program: Ph.D.

Advisor: Dr. Sarah Adamowicz

 

Research:

Biodiversity is important for ecosystem function. Building large and comprehensive phylogenetic trees, i.e., reconstructing the evolutionary relatedness among species, is valuable for diverse studies, including biomonitoring, evolutionary biology, and conservation biology. With phylogenetic trees, we can ask: how much unique evolutionary history is represented at a given site? High-throughput sequencing technologies are providing a great opportunity to build larger trees than ever before, but there is a gap in the literature regarding the performance of existing bioinformatics tools. Therefore, the objective of this study is to test and develop new approaches for quantifying evolutionary history and identifying biodiversity using molecular data. My approach is to combine the best of two methods: DNA barcoding projects sequence many species for few genes, while phylogenomics projects study few species for many genes. I am benchmarking existing methods for phylogenetic placement, including distance-based and likelihood-based methods, considering the taxonomic coverage of backbone phylogenies, phylogenetic patterns in missing data, and generality of the findings across animal taxa. In combining these techniques, this project will open new avenues for biodiversity, evolutionary, and conservation research in species-rich groups of life and under-studied environments.

Nadin Ibrahim

Nadin Ibrahim

Program: M.Sc.

Advisors: Dr. Sarah Adamowicz, Dr. Stefan Kremer

 

Research:

Using high-throughput sequencing (HTS), we can use a technique known as DNA barcoding to identify specimens to species and to discover new species. For animals, barcoding involves a region of the mitochondrial cytochrome c oxidase subunit I gene (COI). However, the error rates for HTS are often quite high. For this reason, creating tools that can correct such errors is of crucial importance. I will create a denoising tool to detect and correct substitution sequencing errors, specifically for the COI gene. This can be accomplished with the use of a convolutional neural network, a deep learning algorithm that is often used to analyze visual imagery but has recently also been used for problems in genomics such as variant calling from sequence data. The tool could be made accessible as a package for programming languages like R or Python.

Jacqueline May

Jacqueline May

Program: Ph.D.

Advisors: Dr. Sarah Adamowicz, Dr. Zeny Feng

 

Research:

Common evolutionary trends have been identified in the genomes of diverse taxonomic groups and have been linked to organismal traits. The substantial increase in the amount of available biological data due to advancements in sequencing technology offers unprecedented opportunities to examine these trends at deeper levels. My research entails identifying the sources of molecular evolutionary rate variation across diverse taxonomic groups and different genetic regions. Another project I am working on addresses the issue of missing values in trait datasets through use of phylogenetically-informed imputation techniques. Imputation techniques offer an alternative to removing cases with missing values from datasets and can contribute to trait-based analyses.

Amanda Meuser

Amanda Meuser

Program: M.Sc.

Advisor: Dr. Elizabeth Mandeville

 

Research:

I completed my undergraduate degree at the University of Guelph in 2017 where I received my BSc (Honours) in Molecular Biology and Genetics. I am now working on my MSc degree in Bioinformatics in the lab of Dr. Elizabeth Mandeville. I am studying the impact of anthropogenic disturbance on freshwater minnow hybridization, specifically in creek chub fish (Semotilus atromaculatus) and its associates.

Matthew Orton

Program: Ph.D.

Advisor: Dr. Sarah Adamowicz

 

Research:

My Masters research is focused primarily on developing software pipelines for the analysis of DNA barcoding data from BOLD.  Current research focuses on:

  • Informatics approaches to studying the relationship between rates of molecular evolution and the latitudinal biodiversity gradient using geographical coordinate data and COI barcoding data.
  • Informatics approaches to studying Arctic Dipteran bio-geography and community similarity across the regions of Canada, Greenland and Norway.
  • Development and field validation of software used in primer design of in-situ qPCR assays of Trichopteran species in Churchill, Mb.

Andrew Riley

Program: Ph.D.

Advisors: Dr. Steffen Graether, Dr. Dan Ashlock

 

Research:

My research involves determining the evolutionary origins of dehydrins, which are intrinsically disordered plant proteins associated with osmotic stress.

Amanda Saunders

Program: Ph.D.

Advisor: Dr. Dan Ashlock

 

Research:

Investigating alternatives to previous hierarchical clustering methods in an attempt to improve the stability of output trees.  This includes exploring the new Bubble Clustering algorithm developed for my Masters as well as exploring possible alternative methods for measuring the association between points.