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aheifets

HN member
Joined
Tue, May 20, 2014, 4:14 PM UTC
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22 items

About aheifets

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Recent public activity

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  3. comment
    Comment #17906424

    Atomwise (YC W15) | Infrastructure, DevOps, Machine Learning | San Francisco | Full-time | Onsite | https://www.atomwise.com/careers/ Atomwise Inc. patented the first deep learning…

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    Comment #17668453

    Atomwise (YC W15) | Infrastructure, DevOps, Machine Learning | San Francisco | Full-time | Onsite | https://www.atomwise.com/careers/ Atomwise Inc. patented the first deep learning…

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    Comment #17498406

    That's a very useful tool! Part of the reason that we launched the Atomwise AIMS program http://www.atomwise.com/aims-awards/ was to address the cost of compounds, in addition to t…

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    Comment #10653393

    I haven't thought about it closely but, from a cursory read, it sounds like the SquareList data structure: http://www.drdobbs.com/database/the-squarelist-data-structur...

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    Comment #10396028

    AutoDock Smina is referenced in the paper, and its source is available under GPLv2: http://sourceforge.net/projects/smina/ If you're interested in open source for deep learning, th…

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    Comment #10390463

    Thanks for the link! I answered some questions about our technique earlier ( https://news.ycombinator.com/item?id=9157777 ), which may help elucidate context.

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    Comment #10153064

    Atomwise (YC W15) | San Francisco | Full time, ONSITE | Deep Learning, Computational Chemistry Atomwise uses deep neural networks to help discover new medicines. Our customers are …

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    Comment #9996340

    Atomwise (YC W15) | San Francisco | Full time, ONSITE | Deep Learning, Computational Chemistry Atomwise uses deep neural networks to help discover new medicines. Our customers are …

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    Comment #9164761

    Thank you! Personally, I find it very exciting to be working on these problems. With respect to boosting, we have more investigation to do, of course; the tricky issue with the bio…

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    Comment #9164748

    Today, those tests are done physically. But, you're right: if you have a good system to tell if a molecule will stick to a given protein, there's no reason to constrain your tests …

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    Comment #9161491

    The typical timeline to get an actual cure all the way through the drug discovery pipeline is about 14 years. While we haven't been around long enough for that, we have had our alg…

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    Comment #9161478

    Great questions! The typical input to the neural network is the 3D structure of the molecule and of the protein. The model works by detecting patterns in the pair of protein and th…

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    Comment #9161401

    New medical discoveries aside, we're seeing self-driving cars and speech recognition that runs on a cell phone. I grew up reading about those kinds of things in Asimov, so I person…

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    Comment #9161392

    Thank you for the kind wishes! Over the past few years, there's been a huge increase in the amount of data available for this kind of machine learning. We curate our data from a nu…

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    Comment #9161363

    As you might expect, there are trade-offs, and it's a question of picking the right tool for the job. My understanding of D.E. Shaw's approach is that they're doing molecular dynam…

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    Comment #9159821

    I’m the cofounder and CEO of Atomwise and, since this is Hacker News, I thought I’d cover the technical details a bit more: We run deep neural networks on one of the biggest superc…

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