Welcome to the Tahiri Lab

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We are a dynamic research group within the Department of Computer Science at the University of Sherbrooke.

Our lab focuses on transdisciplinary research aimed at understanding species evolution. By developing advanced metrics and algorithms for phylogenetic and lineage trees, we analyze genetic information in conjunction with climatic and other ecological parameters to reveal deeper insights into evolutionary processes.

We are looking for passionate new PhD students, Postdocs, and Master students to join the team (more info) !

MISSION

The research of Professor Nadia Tahiri focuses on establishing robust mathematical and statistical foundations to address the complex problem of phylogenetic tree classification and clustering. She is also dedicated to developing an open-source platform for biologists, enabling them to apply these cutting-edge methods. This work involves defining new optimization criteria for constructing multiple alternative consensus and supertrees using clustering algorithms and key phylogenetic tree metrics.

Our lab research is centered around three key objectives to build a computational framework for studying gene evolution:

1. Development of efficient algorithms to classify and construct a set of plausible alternative consensus and supertrees that accurately represent the data.
2. Investigation of evolutionary patterns in Aminoacyl-tRNA synthetases to uncover deeper biological insights.
3. Design and implementation of an open-source software platform that will contain all algorithms developed in our lab, alongside both real and simulated datasets.

The long-term goal of our lab is to create an innovative, systematic, and automated approach for reconstructing diverse scenarios of genetic evolution in species groups affected by reticulate evolutionary events. This research will significantly contribute to the inference of alternative subtrees within the tree of life, providing valuable insights into the biodiversity and evolutionary relationships of all living organisms.

RESEARCH INTERESTS

• Bioinformatics
• Evolutionary biology
• Phylogeny
• Evolution
• Phylogeography
• Classification
• Clustering
• Algorithms

ACKNOWLEDGEMENTS

We are grateful for funding from the University of Sherbrooke, the Fonds de recherche du Québec – Nature et technologies (FRQNT), and the Natural Sciences and Engineering Research Council of Canada (NSERC).