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When you hear the words Alzheimer's disease, what do you think of? The truth is, the picture most of us have of the disease is incomplete. Alzheimer's disease doesn't start when someone starts to lose their memory. It actually starts years – sometimes decades – earlier. The Rethinking Alzheimer's Disease Podcast is an engaging, narrative-style podcast miniseries for those curious or motivated to learn about Alzheimer’s disease. Perhaps you have a family member with Alzheimer’s disease, or ca ...
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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 [email protected] or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast.
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