>> Live from Washington D.C., it's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you by Amazon Web Services and its ecosystem partners. (upbeat music) >> Hey welcome back everyone we're here live in Washington D.C. for Amazon Web Services Public Sector Summit, I'm John Furrier. Stu Miniman our next guest is Dr. Swaine Chen, Senior Research Scientist of Infectious Disease, the Genome institute of Singapore. And also an assistant professor at The Medicinal National University of Singapore. Great to have you on, I know you've been super busy, you were on stage yesterday, we tried to get you on today, thanks for coming in and kind of bring it in to our two days of coverage here. >> Thank you for having me, I'm very excited to be here. >> So we were in between breaks here and we're talking about some of the work around DNA sequencing but, you know it's super fascinating. I know you've done some work there but, I want to talk first about your presence here at the Public Sector Summit. You were on stage, tell your story 'cause you have an very interesting presentation around some of the cool things you're doing in the cloud, take a minute to explain. >> That's right, so one of the big things that's happening in genomics is the rate of data acquisition is outstripping Moore's Law right? So for a single institute to try to keep up with compute for that, we really can't do it. So that really is the big driver for us to move to cloud, and why we're on AWS. And so then, of course once we can do that once we can sort of have this capacity, there's lots of things that my research is mostly on infection diseases, so one of the things where really you've got, all of a sudden, you've got a huge amount of data you need to process would be a case like an outbreak. And that just happens it happens unexpectedly. So we had one of these that happened that I talked about. And the keynote yesterday was on Group B Streptococcus. This is a totally unexpected disease. And so all of a sudden we had all this data we had to process, and try to figure out what was going on with that outbreak. And unfortunately we're pretty sure that there's going to be other outbreaks coming up in the future as well, and just, being able to be prepared for that. AWS helps us provide some of that capacity, and we're you know, continuously trying to upgrade our analytics for that as well. >> So give me an example of kind of where this kind of hits home for you, where it works. What is doing specifically? Is it changing the timeframe? Is it changing the analysis? Where is the impact for you? >> Yeah so it's all of this right? So it's all the sort of standard things that AWS is providing all of the other companies. So it's cheaper for us to just pay for what we use, especially when we have super spiky work loads. Like in the case of an outbreak right? If all of a sudden we need to sort of take over the cluster internally, well there's going to be a lot of people screaming about that, right? So we can kick that out to the cloud, just pay for what we use, we don't have to sort of requisition all the hardware to do that, so it really helps us along these things. And also gives us the capacity too think about you know as data just comes in more and more, we start to think about, lets just increase our scale. This is somethings that been happening, sort of incessantly in science, incessantly in genomics. So as just an example from my work and my lab we're studying infectious diseases we're studying mostly bacterial genomics. So the genomes of bacteria that cause infections. We've increased our scale 100x in the last four years in terms of the data sets that we're processing. And we see the samples coming in, we're going to do another 10x in the next two years. We just really wouldn't have been able to do that on our current hardware. >> Yeah, Dr. Chen, fascinating space. We love for years there was discussion of well oh how much it costs, to be able to do everything had gone down. But what has been fascinating is you've look, you've talked about that date and outstripping Moore's Law, and not only what you can do but in collaboration with others now, because there's many others around the globe that are doing this. 'Cause talk about that level of data, and how the cloud enables that. >> Yeah so that's actually another great point. So genomics is very strong into open source, especially in the academic community. Whenever we publish a paper, all the genomic data that's in that paper, it gets, uh oh (laughs). Whenever we, whenever we publish-- >> Mall's closing in three minutes. >> Three minutes cloud count. >> Three minutes, okay. Whenever we publish a paper, that data goes up and gets submitted to these public databases. So when I talk about 100x scale, that's really incorporating world wide globally all the data that's present for that species. So as an example, I talked about Group B Streptococcus, another bacteria we study a lot is E. coli, Escherichia coli. So that causes diarrhea, it causes urinary tract infections, bloodstream infections. When we pull down a data set locally, in Singapore, with 100, 200, 300 strains we can now integrate that with a global database of 10,000, 20,000 strains and just gain a global prospective on that. We get higher resolution, and really AWS helps us to pull in from these public databases, and gives the scale to burst out that processing of that many more strains. >> So the DNA piece of your work, does that tie into this at all? I mean obviously you've done a lot of work with the DNA side, was that playing into this as well? >> The? >> The DNA work, you've done in the past? >> Yeah so all of the stuff that we're doing is DNA, basically. So there are other frontiers, that have been explored quite a lot. So looking at RNA and looking at proteins and carbohydrates and lipids, but at the Genome Institute in Singapore, we're very focused on the genetics, and mostly are doing DNA. >> How has the culture changed from academic communities with cloud computing. We're seeing sharing, certainly a key part of data sharing. Can you talk about that dynamic, and what's different now than it was say five to even 10 years ago? >> Huh, I'd say that the academic community has always been pretty open, the academic community right? It's always been a very strong open source compatible kind of community right? So data was always supposed to be submitted to public databases. Didn't always happen, but I think as the data scale goes up and we see the value of the sort of having a global perspective on infectious diseases and looking for the source of an outbreak, the imperative to share data right? That looking at outbreaks like Ebola, where in the past people might try to hold data back because they wanted to publish that. But from a public health point of view, the imperative to share that data immediately is much stronger now that we see the value of having that out there. So I would say that's one of the biggest changes is the imperative is there more. >> I agree I think academic people I talk to, they always want to share, it might be not uploaded fast enough. So time is key. But I got to ask you a personal question, of all the work you've done on, you've seen a lot of outbreaks. This is kind of like scary stuff. Have you had those aha moments, just like mind blowing moments where you go, oh my God we did that because of the cloud? I mean an you point to some examples where it's like that is awesome, that's great stuff. >> Well so we certainly have quite a few examples. I mean outbreaks are just unexpected. Figuring out any of them and being able to impact, or sort of say this is how this transmission is, or this is what the source is. This is how we should try to control this outbreak. I mean all of those are great stories. I would say that , you know, to be honest were still early in our transition to the cloud, and we're kind of running a hybrid environment right now. Like really when we need to burst out, then we'll do that with the cloud. But most of our examples, so far, you know we're still early in this for cloud. >> To the spiky is the key value for you, when the hits pipe out. >> So what excited you about the future of the technology that, do you believe we'll be able to do as we just accelerate, prices go down, access to more information, access to more. What do you think we're going to see in this field the next, you know, one to three years? >> Oh I think on of the biggest changes that's going to happen, is we're going to shift completely how we do, for example in outbreaks right? We're going to shift completely how we do outbreak detection. It's already happening in the U.S. and Europe. We're trying to implement this in Singapore as well. Basically the way we detect outbreaks right now, is we see a rise in the number of cases, you see it at the hospitals, you see a cluster of cases of people getting sick. And what defines a cluster? You kind of need enough of these cases that it sort of statistically goes above your base line. But we actually, when we look at genomic data we can tell, we can find clusters of outbreaks that are buried in the baseline. Because we just have higher resolution. We can see the same bacteria causing infections in groups of people. It might be a small outbreak, it might be self limited. But we can see this stuff happening, and it's buried below the baseline. So this is really what's going to happen, is instead of waiting until, a bunch of people get sick before you know that there's an outbreak. We're going to see that in the baseline or as it's coming up with two, three, five cases. We can save hundreds of infections. And that's one of the things that's super exciting about moving towards the future where sequencing is just going to be a lot cheaper. Sequencing will be faster. Yeah it's a super exciting time. >> And more researching is a flywheel. More researching come over the top. >> Yep, exactly, exactly. >> That's great work, Dr. Swaine Chen, thanks for coming on theCUBE. We really appreciate-- >> No thank you. >> Congratulations, great talk on the keynote yesterday, really appreciate it. This is theCUBE bringing you all the action here as we close down our reporting. They're going to shut us down. theCUBE will go on until they pull the plug, literally. Thanks for watching, I'm John Ferrier, Stu Miniman, and Dave Vellante. Amazons Web Services Public Sector Summit, thanks for watching. (upbeat techno music)