On AIRR 13: Disease diagnostics using machine learning with Maxim Zaslavsky and Dr. Scott D. Boyd
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On AIRR 13: Disease diagnostics using machine learning with Maxim Zaslavsky and Dr. Scott D. Boyd
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À propos de cet audio
Maxim Zaslavsky is a computer scientist using machine learning to address problems in immunology. He is currently PhD student at Stanford University.
Scott D. Boyd is a physician-scientist and Professor of Pathology and of Food Allergy and Immunology at Stanford University. His group is focused on using high-throughput DNA sequencing and single-cell experiments to analyse human immune responses to infection and vaccination.
We discuss the preprint “Disease diagnostics using machine learning of immune receptors”, available at BioRxiv: https://doi.org/10.1101/2022.04.26.489314. The work is led by Maxim Zaslavsky with Scott Boyd the corresponding author. In the manuscript, the authors demonstrate how AIRR-seq and machine learning can be used in disease diagnostics.
The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding.
Comments are welcome to the inbox of onairr@airr-community.org or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast.