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Does anyone know why this approach is "viewed as a rogue project by the immunology community"? Is it just because it's new, or is there something more fundamental that conflicts with established immunology?



Hi all, this is Naveen from Immunity Project YC team. The fact that we are using ML to identify epitopes that are the preferred targets on the virus for HIV controllers is key to what makes our project unique. This is a newer approach for developing a vaccine and therefore makes it "rogue."


By the way. That "rouge" approach is what would I have go through as a sysadmin if this was an computer related problem. I think you deserve to be a case study in immunology and be very very successful.

Sometimes thinking out of the box and letting go of established ways will lead to results.

Edit: Also in computer sciences we use differentiating between two known states to find out how to change on state to the other one perfectly. In immunology do you use similar approaches?


Hey Naveen, I know that there are some epitopes that can only be recognized if there's a weird domain swap that happens, causing antibodies to be "four-pronged" instead of "two pronged". I think it's a proline substitution in the conserved neck region. Did you screen out those epitopes from your ML?

Also good luck! I'm chipping in now. I'm relaunching my own crowd-funded nonprofit research in the biomedical space (and will be partnering with crowdhoster/crowdtilt)... I'm magnifying your message. When the dust settles a little bit I'd love to be in touch with you guys.


Good luck with your relaunch! I'll look for it, so I can support it again!


I can easily find plenty of papers using ML for HIV epitope analysis.


Mind linking to a few you find particularly insightful? I'm sure many of us would be more than appreciative.


This sounds pretty fascinating. Do you have any links/resources that dives more in depth into this approach?


This talk at GitHub makes good watching http://www.youtube.com/watch?v=8syV5t2_3QI&feature=youtu.be


[deleted]


Yes, it stands for machine learning. The one comment I saw the phrase "Mind linking" in looks as if it was short for "Do you mind linking to...".


mainly because lots of money and time got wasted in finding a vaccine. HIV vaccine would be very very risky to use thats why research is looking for a cure




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