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เนื้อหาจัดทำโดย Jeremy Daly and Rebecca Marshburn เนื้อหาพอดแคสต์ทั้งหมด รวมถึงตอน กราฟิก และคำอธิบายพอดแคสต์ได้รับการอัปโหลดและจัดเตรียมโดย Jeremy Daly and Rebecca Marshburn หรือพันธมิตรแพลตฟอร์มพอดแคสต์โดยตรง หากคุณเชื่อว่ามีบุคคลอื่นใช้งานที่มีลิขสิทธิ์ของคุณโดยไม่ได้รับอนุญาต คุณสามารถปฏิบัติตามขั้นตอนที่อธิบายไว้ที่นี่ https://th.player.fm/legal
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Episode #94: Serverless for Scientific Research with Denis Bauer

50:43
 
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Manage episode 288596644 series 2516108
เนื้อหาจัดทำโดย Jeremy Daly and Rebecca Marshburn เนื้อหาพอดแคสต์ทั้งหมด รวมถึงตอน กราฟิก และคำอธิบายพอดแคสต์ได้รับการอัปโหลดและจัดเตรียมโดย Jeremy Daly and Rebecca Marshburn หรือพันธมิตรแพลตฟอร์มพอดแคสต์โดยตรง หากคุณเชื่อว่ามีบุคคลอื่นใช้งานที่มีลิขสิทธิ์ของคุณโดยไม่ได้รับอนุญาต คุณสามารถปฏิบัติตามขั้นตอนที่อธิบายไว้ที่นี่ https://th.player.fm/legal

About Denis Bauer

Dr. Denis Bauer is an internationally recognized expert in artificial intelligence, who is passionate about improving health by understanding the secrets in our genome using cloud-computing technology. She is CSIRO’s Principal Research Scientist in transformational bioinformatics and adjunct associate professor at Macquarie University. She keynotes international IT, LifeScience, and Medical conferences and is an AWS Data Hero, determined to bridge the gap between academe and industry. To date, she has attracted more than $31M to further health research and digital applications. Her achievements include developing open-source bioinformatics software to detect new disease genes and developing computational tools to track, monitor, and diagnose emerging diseases, such as COVID-19.

Watch this episode on YouTube: https://youtu.be/5MGxgYd93Jw

This episode sponsored by New Relic.

Transcript:

Jeremy: Hi everyone. I'm Jeremy Daly, and this is Serverless Chats. Today, I'm chatting with Denis Bauer. Hey, Denis, thanks for joining me.

Denis: Thanks for having me. Great to be on your show.

Jeremy: So you are a Group Lead at CSIRO and an Honorary Associate Professor at Macquarie University in Sydney, Australia. So I would love it if you could explain and tell the listeners a little bit about your background and what CSIRO does.

Denis: Yeah. CSIRO is Australia's government research agency and Macquarie University is one of Australia's Ivy League universities. They've been working together on really translating research into products that people can use in their everyday life. Specifically, they worked together in order to invent WiFi, which is now used in 5 billion devices worldwide. CSIRO has also collaborated with other universities, for example, has developed the first treatment for influenza. And on a lighter note has developed a recipe book, the Total Wellbeing Diet book, which is now on the book bestseller list alongside Harry Potter and The Da Vinci Code. From that perspective CSIRO really has this nice balance between product that people need and product that people enjoy.

Jeremy: Right. And what's your background?

Denis: So my background is in bioinformatics, which means that in my undergraduate, I was together with the students that did IT courses, math, stats, as well as medicine and molecular biology and then in the last year of the study all of this was brought together and sort of a specialized way of really focusing on what bioinformatics is. Which is using computers, back in the days it was high-performance compute, in order to analyze massive amounts of life science data. Today, this is of course, cloud computing for me at least.

Jeremy: Right. Well, that's pretty amazing. Today's episode ... I've seen you talk a number of times all remotely, unfortunately. I hope one day that I'll be able to see you speak in-person when we can start traveling again. I've seen you speaking a lot about the scientific research that's being done and the work the CSIRO doing and more specifically, how you're doing it with serverless and how serverless is sort of enabling you to do some of these things in a way that probably was only possible for really large institutions in the past. I want to focus this episode really on this idea of serverless for scientific research. We're going to talk about COVID later, we can talk about a couple of other things, but really it's a much broader thing. I had a conversation with Lynn Langit before, we were talking about Big Data and the role that plays in genomics and some of these other things and how just the cloud accelerates people's ability to do that. Maybe we can start before we get into the serverless part of this. We could just kind of take step back and you could give me a little bit more context on the type of research that you and your organization has been doing.

Denis: Yeah. So my group is the Transformational Bioinformatics Team. So again, it's translating research into something that affects the real world. In our case that usually is medical practice because we want to research human health and improve disease treatment and all this management going forward and for that data is really critical. It's sort of the one thing that separates a hunch from actually something that you can point to and say, "Okay, this is evidence moving forward," and from there you can incrementally improve and you know that you're going in the right direction rather than just exploring the space.

Jeremy: Right. And you mentioned data again. Data is one of those things where, and I know this is something you mentioned in your talks, where the importance of data or the amount of data and what you can do with that is becoming almost as important, if not just as important, as the actual clinicians on the frontline actually treating disease. So can you expand upon that a little bit? What role does data play? And maybe you could give us an example of where data helped make better decisions.

Denis: Yeah. So a very recent example is of course with COVID, where no one knew anything really at the beginning. I mean, coronaviruses were studied, but not to that extent. So the information that we had beginning of a pandemic were very basic. From that perspective, when you know nothing about a disease, the first thing you need to do is collect information. Back then, we did not have that information and actions were needed. So some of the decisions that had to be made back then were based on those hunches and those previous assumptions that were made about other diseases. So for example, in the UK they define their strategy based on how influenza behaved and how it spread and we now know that it's vastly different, how influenza is spreading and how coronavirus is spreading. So therefore in the course of the action more research was done and based on that, they adjusted, probably the whole world adjusted how they managed or interfered with the disease. We now know that whatever we did at the beginning was not as good as what we're doing now, so therefore data is absolutely critical.

Jeremy: Right. And the problem with medical data, I would assume, is one, that it's massive, right? There's just so much of it out there. When we're going to start talking about genomics and gene sequencing and things like that, I can imagine there's a lot of data in every sample there. And so, you've got this massive amount of data that you need to deal with. I do want to get into that a little bit. Maybe we can start getting into this idea of sort of genome editing and things like that and where serverless fits in there.

Denis: Yeah, absolutely. So my group researches two different areas. One is genome analysis where we try to understand disease genes, predict risk, for example, of developing heart disease, diabetes, in the future, but the other element is around doing something, treating actual patients with newer technology, and this is where genome editing or genomic surgery comes in, where the aim is to cure diseases that previously thought to be incurable genetic diseases. The aim of geno...

  continue reading

142 ตอน

Artwork
iconแบ่งปัน
 
Manage episode 288596644 series 2516108
เนื้อหาจัดทำโดย Jeremy Daly and Rebecca Marshburn เนื้อหาพอดแคสต์ทั้งหมด รวมถึงตอน กราฟิก และคำอธิบายพอดแคสต์ได้รับการอัปโหลดและจัดเตรียมโดย Jeremy Daly and Rebecca Marshburn หรือพันธมิตรแพลตฟอร์มพอดแคสต์โดยตรง หากคุณเชื่อว่ามีบุคคลอื่นใช้งานที่มีลิขสิทธิ์ของคุณโดยไม่ได้รับอนุญาต คุณสามารถปฏิบัติตามขั้นตอนที่อธิบายไว้ที่นี่ https://th.player.fm/legal

About Denis Bauer

Dr. Denis Bauer is an internationally recognized expert in artificial intelligence, who is passionate about improving health by understanding the secrets in our genome using cloud-computing technology. She is CSIRO’s Principal Research Scientist in transformational bioinformatics and adjunct associate professor at Macquarie University. She keynotes international IT, LifeScience, and Medical conferences and is an AWS Data Hero, determined to bridge the gap between academe and industry. To date, she has attracted more than $31M to further health research and digital applications. Her achievements include developing open-source bioinformatics software to detect new disease genes and developing computational tools to track, monitor, and diagnose emerging diseases, such as COVID-19.

Watch this episode on YouTube: https://youtu.be/5MGxgYd93Jw

This episode sponsored by New Relic.

Transcript:

Jeremy: Hi everyone. I'm Jeremy Daly, and this is Serverless Chats. Today, I'm chatting with Denis Bauer. Hey, Denis, thanks for joining me.

Denis: Thanks for having me. Great to be on your show.

Jeremy: So you are a Group Lead at CSIRO and an Honorary Associate Professor at Macquarie University in Sydney, Australia. So I would love it if you could explain and tell the listeners a little bit about your background and what CSIRO does.

Denis: Yeah. CSIRO is Australia's government research agency and Macquarie University is one of Australia's Ivy League universities. They've been working together on really translating research into products that people can use in their everyday life. Specifically, they worked together in order to invent WiFi, which is now used in 5 billion devices worldwide. CSIRO has also collaborated with other universities, for example, has developed the first treatment for influenza. And on a lighter note has developed a recipe book, the Total Wellbeing Diet book, which is now on the book bestseller list alongside Harry Potter and The Da Vinci Code. From that perspective CSIRO really has this nice balance between product that people need and product that people enjoy.

Jeremy: Right. And what's your background?

Denis: So my background is in bioinformatics, which means that in my undergraduate, I was together with the students that did IT courses, math, stats, as well as medicine and molecular biology and then in the last year of the study all of this was brought together and sort of a specialized way of really focusing on what bioinformatics is. Which is using computers, back in the days it was high-performance compute, in order to analyze massive amounts of life science data. Today, this is of course, cloud computing for me at least.

Jeremy: Right. Well, that's pretty amazing. Today's episode ... I've seen you talk a number of times all remotely, unfortunately. I hope one day that I'll be able to see you speak in-person when we can start traveling again. I've seen you speaking a lot about the scientific research that's being done and the work the CSIRO doing and more specifically, how you're doing it with serverless and how serverless is sort of enabling you to do some of these things in a way that probably was only possible for really large institutions in the past. I want to focus this episode really on this idea of serverless for scientific research. We're going to talk about COVID later, we can talk about a couple of other things, but really it's a much broader thing. I had a conversation with Lynn Langit before, we were talking about Big Data and the role that plays in genomics and some of these other things and how just the cloud accelerates people's ability to do that. Maybe we can start before we get into the serverless part of this. We could just kind of take step back and you could give me a little bit more context on the type of research that you and your organization has been doing.

Denis: Yeah. So my group is the Transformational Bioinformatics Team. So again, it's translating research into something that affects the real world. In our case that usually is medical practice because we want to research human health and improve disease treatment and all this management going forward and for that data is really critical. It's sort of the one thing that separates a hunch from actually something that you can point to and say, "Okay, this is evidence moving forward," and from there you can incrementally improve and you know that you're going in the right direction rather than just exploring the space.

Jeremy: Right. And you mentioned data again. Data is one of those things where, and I know this is something you mentioned in your talks, where the importance of data or the amount of data and what you can do with that is becoming almost as important, if not just as important, as the actual clinicians on the frontline actually treating disease. So can you expand upon that a little bit? What role does data play? And maybe you could give us an example of where data helped make better decisions.

Denis: Yeah. So a very recent example is of course with COVID, where no one knew anything really at the beginning. I mean, coronaviruses were studied, but not to that extent. So the information that we had beginning of a pandemic were very basic. From that perspective, when you know nothing about a disease, the first thing you need to do is collect information. Back then, we did not have that information and actions were needed. So some of the decisions that had to be made back then were based on those hunches and those previous assumptions that were made about other diseases. So for example, in the UK they define their strategy based on how influenza behaved and how it spread and we now know that it's vastly different, how influenza is spreading and how coronavirus is spreading. So therefore in the course of the action more research was done and based on that, they adjusted, probably the whole world adjusted how they managed or interfered with the disease. We now know that whatever we did at the beginning was not as good as what we're doing now, so therefore data is absolutely critical.

Jeremy: Right. And the problem with medical data, I would assume, is one, that it's massive, right? There's just so much of it out there. When we're going to start talking about genomics and gene sequencing and things like that, I can imagine there's a lot of data in every sample there. And so, you've got this massive amount of data that you need to deal with. I do want to get into that a little bit. Maybe we can start getting into this idea of sort of genome editing and things like that and where serverless fits in there.

Denis: Yeah, absolutely. So my group researches two different areas. One is genome analysis where we try to understand disease genes, predict risk, for example, of developing heart disease, diabetes, in the future, but the other element is around doing something, treating actual patients with newer technology, and this is where genome editing or genomic surgery comes in, where the aim is to cure diseases that previously thought to be incurable genetic diseases. The aim of geno...

  continue reading

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