EPISODE · Nov 21, 2024 · 11 MIN
132 Unlocking the Secrets of Antimicrobial Resistance in Metagenomes
from Micro binfie podcast · host Microbial Bioinformatics
In this episode of the Micro Binfie podcast, host Andrew Page is live from the 10th Microbial Bioinformatics Hackathon in Bethesda, Maryland. He sits down with David Mahoney, a PhD student from Dalhousie University in Halifax, Nova Scotia. David shares his research on characterizing antimicrobial resistance (AMR) genes and their transfer within metagenomes, focusing on metagenomic assembly graphs. They delve into David’s background in food safety microbiology and his interest in the public health implications of genomics. He explains his exciting work on analyzing how AMR genes transfer across different environments, such as food production plants and clinical settings, using both new and existing data from Canada’s Genomics Research and Development Initiative. David also highlights his use of innovative methods like assembly graphs and graph-based approaches to uncover AMR gene flow and lateral gene transfers, including the potential of machine learning techniques such as graph convolutional neural networks.
What this episode covers
In this episode of the Micro Binfie podcast, host Andrew Page is live from the 10th Microbial Bioinformatics Hackathon in Bethesda, Maryland. He sits down with David Mahoney, a PhD student from Dalhousie University in Halifax, Nova Scotia. David shares his research on characterizing antimicrobial resistance (AMR) genes and their transfer within metagenomes, focusing on metagenomic assembly graphs. They delve into David’s background in food safety microbiology and his interest in the public health implications of genomics. He explains his exciting work on analyzing how AMR genes transfer across different environments, such as food production plants and clinical settings, using both new and existing data from Canada’s Genomics Research and Development Initiative. David also highlights his use of innovative methods like assembly graphs and graph-based approaches to uncover AMR gene flow and lateral gene transfers, including the potential of machine learning techniques such as graph convolutional neural networks.
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132 Unlocking the Secrets of Antimicrobial Resistance in Metagenomes
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