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A primer on ML in antibody engineering

abhishaike.com · 7,601 words · saved by 2 readers

I increasingly see that a fair bit of the progress in ML-based protein design methods is occurring in antibody engineering, which is the process of creating antibodies tailor-made to bind to specific things in the body. I've noticed this phenomenon for the past year, and never quite understood what was going on in the space. I've been recently taking the time to better understand this whole field a bit more and made a post about it to cement what I've learned. To note, this is not a machine-learning post in a traditional sense. I won't be going into the exact details of how antibody ML methods exactly work, but rather setting up the contextual knowledge needed to understand these methods at all + going through a few antibody ML papers. I'm posting this picture right now so you have a place to refer back to it later. Ignore it for now, but it'll probably be useful down the road. The immune system is one of those things that is, unfortunately, impossible to understand unless you know all

Primers A primer on machine learning in antibody engineering 7.4k words, 34 minutes reading time Abhishaike Mahajan Apr 15, 2024 48 2 Share Note: per October 30th, 2024, I don’t think this post was ever actually emailed to anyone, and all traffic to this was via my Twitter . This was actually written on April 14th, 2024. So, if you’ve already read this, feel free to ignore it! But, if not, and you’re curious about why so many ML-bio companies seem to be antibody design companies + how it works internally, read on! Introduction Antibody background What is an antibody? Antibody structure Antibod

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