PhD Seminar • Bioinformatics • Unsupervised and Self-Supervised Learning Approaches to Taxonomic Categorization of DNA SequencesExport this event to calendar

Thursday, April 18, 2024 — 2:30 PM to 3:30 PM EDT

Please note: This PhD seminar will take place online, NOT in person as advertised earlier.

Pablo Millán Arias, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Lila Kari

This talk discusses two approaches for utilizing unlabelled genomic data for taxonomic categorization, specifically through deep-learning-based algorithms. First, we introduce an entropy-based clustering method for DNA Sequences, which employs a discriminative classifier to identify taxonomic clusters without supervision. Further, we expand upon these ideas and leverage self-supervised representation learning for enhanced non-parametric DNA sequence clustering, achieving performance comparable to traditional alignment-based methods in synthetic datasets. Our work demonstrates the integration of deep unsupervised learning with taxonomic identification, offering novel approaches for biodiversity studies.


To attend this PhD seminar on Zoom, please go to https://uwaterloo.zoom.us/j/94291355426.

Location 
DC - William G. Davis Computer Research Centre
Online PhD seminar
200 University Avenue West

Waterloo, ON N2L 3G1
Canada
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