If you listened to our episode focused on science communication featuring proteomics leaders Ben Orsburn Ph.D. and Ben Neely Ph.D., then you've already heard about their excellent podcast, The Proteomics Show. On The Proteomics Show, they interview researchers in the proteomics community to learn about their motivations, their backstories, and their work. Today, we're sharing an episode of The Proteomics Show where the Bens interview Translating Proteomics host Parag Mallick. Check it out to learn about Parag's journey to proteomics, his efforts advocating for open data sharing, and his work as a professional magician.

After listening, be sure to check out more episodes of The Proteomics Show on their feed where you'll find over 70 interviews with many, many interesting people in the proteomics community. Find their feed here:

https://us-hupo.org/Podcasts

Hey, everyone.

Parag here.

Today we are sharing an episode from another fantastic proteomics focused podcast, the Proteomics Show.

If you listen to our translating Proteomics episode focused on science communication, you already met the hosts of the Proteomics show, Ben Osborne and Ben Neely.

Both are leaders in the proteomics community in their own right.

And on their podcast, they interview proteomics researchers to learn about their backgrounds, their motivations and their work.

In the episode we're sharing today, they interviewed me, but I highly encourage you to head over to their feed where you'll find over 70 episodes featuring conversations with many, many interesting people.

With that, here are the bends.

Enjoy.

Hello and welcome to this week's the Proteomics Show.

This is the Oregon Trail season three of a special limited series sponsored by USUPO.

Hi, I'm Ben Osborne and I'm here with Dr.

Benjamin Neely.

And this week's episode features Dr.

Parag Malik, who is an associate professor at Stanford and also the co founder of Nautilus Biotechnology.

Yeah, this was his story of this would be astronaut turned transformative scientist who may be the most interesting person we've talked to as well as the most humble.

So definitely give it a listen.

Enjoy.

Hello, Parag, thanks for coming today.

Thanks so much for having me.

I'm delighted to be here.

Yeah.

So we had contacted you a while back to have you on and.

And then you went and won an award from us Hupo.

And that means you're actually talking at us Hupo.

What was the award that you won?

I won the Gil.

The Gil Ohman Computational Proteomics Award.

Oh, right.

Yeah.

Okay.

Super cool.

Yeah, that's.

And that's one of those that if you look back on the list of people, it's like they're great and you're great, and so I guess that's the.

Astonishing group of people to be associated with.

And Gil himself is such an amazing, lovely person.

So I, I just, I feel thrilled.

And like, still killing it.

I mean, amazing.

Amazing.

Yes.

Transformed his perspectives on clinical proteomics and how to bring it into the world he's been so laser focused on.

It's.

It's amazing.

It's really amazing.

All right, so you're going to be.

It's normally like a morning talk.

I should probably look at the schedule, who knows?

But I know it's a ways off.

But do you know what?

I bet you know what you're going to be talking about.

Can you tell us a little bit about what you're going to be Talking about.

So I actually, I haven't written the talk yet, and I thought I would do something, you know, different than my usual research talk for it.

In part, the.

What the.

I think part of maybe one of the things that I was part of, unfortunately, was bringing some standardization, bringing Proteo wizard in.

And the story from way back in the day, starting in Rudy's lab with Patrick Pedrioli and his unpacking of what was in a thermo RAW file before it was.

Before you were really able to access those directly, the story of how that evolved and MZ Data and MZ XML came about.

And so I was really hoping to paint a picture of how we got to where we are today and that we have open formats, we have data sharing, and some of the silly challenges along the way had to start a foundation just so that we could actually have open data throughout proteomics and then maybe share a few perspectives about some opportunities that we have as a field going forwards and some.

Some things we might want to think about.

Okay, first off, I want you to talk about all these things, because I don't know them, but I do.

Like, I'm of that generation that had horror stories.

Like, we had.

We had a tripletoff and so Saix and we had this.

Oh, I forgot the guy's name.

But it was like an unofficial reader that would like, export these as MGFs and it would like, recursively.

And then we could use, like, mascot.

Otherwise, like, you had to use Paragon.

And it was.

It was.

Maybe it was Sean Seymour, I don't remember.

But everyone had these, like, readers.

And we would like, call people up like, hey, man, you got.

Do you have that APL reader?

Like, that's in Max Quant version 1.205.

And we'd like, trade them.

It was.

It was like a bootleg.

That was exactly what it was.

And it was such a hindrance to the field because it was isolated.

Everybody had to have a license from the vendor themselves.

Getting those licenses wasn't straightforward necessarily.

Oftentimes there weren't even libraries available to read them.

You had to go through the vendor software and hack around in Visual Basic to make it happen.

And we were really fortunate to first have supported MZML as it was coming about and becoming the reference standard for that.

And then chatting with the different vendors and saying, hey, can we maybe help with conversion of your formats to mzml?

And the first one to sign up was Thermo.

And then.

And they were just both.

It was at a Time where they were excited about opening up access, but they were also nervous about it and there were concerns about what would this mean for compliance about people being able to read or write their files.

And so we went.

And then there was the actual mechanics of how do you actually do it, how do you fold this in, how do you make it easy to use?

And then Saix Shaunc Moore as you mentioned was next and then that really started the train where we were able to get Agilent and Waters and Shimatsu and finally the most exciting moment was when we had all of the major vendors supported and this sort of universal one ring way that you could get access to all of the data.

And, and our, our paper there was really neat because it actually included authors from all of the major vendors and I don't know that that happens terribly often.

It certainly doesn't.

Right.

I, I can't think of another one.

Right, but which was the worst one to, to work with?

Right?

Was it thermo binaries or rights from everybody else or.

No, I think the first hurdle was really just about the concept of open data.

The concept of data being able to be read by anybody whether they had an instrument or not, which sounds really obvious today.

It sounds like well of course you want the data in as many people's hands as possible.

But back then that wasn't the case.

It was like okay, we want people who have thermo instruments to be able to read thermo files.

And so we really had to get over that conceptual intellectual barrier first.

And then in terms of support, I think once we demonstrated the value we demonstrated like oh look, there's a whole set of bioinformaticists going to town on your data and creating tools that are, you know, amazing and are getting more out of your data than you are that the, they saw this incredible leverage and so everybody joined on from then.

And what's, I mean we keep talking about time and I'm horrible at this again fault our research department.

But like what.

So like the Preowizard, this paper where they're all together, what is that time period?

Is that 20?

I mean the teens?

12.

So yeah, so the very first Proteo wizard paper was, was side by side with mcml.

Ish.

2007 somewhere in there and then.

Yeah, and then that was the foundation that was laid and really came about because of my student Darren who was just, you know, he was a card carrying real software engineer and just watching how hard it was to get him into being able to do proteomics, just what tools were available, how hard it was to access the data.

We had all these conversations about, even if you created these file formats, would it be like Blu Ray, where the Blu Ray still ships with a DVD alongside it?

And.

And so it really started there with just how can we make it so that anybody who wants to start doing proteomics data analysis doesn't have this huge lift.

They don't have to figure out how to calculate the mass of a peptide.

They just like call the peptide mass function and it figures it out for you.

And then how do we get the data in?

And so that was the first step.

And then the second was getting direct access to the vendor formats.

And that was.

That was.

I think you're right.

That was in the teens.

I mean, and I'm going to be quiet, but like, again, we actually don't do research on people.

And I have a horrible memory.

This is huge.

Like, I actually had to do something else.

You.

But was like, what were the big things that have happened?

And I think more so than any other advance was that was the open.

Was the open software or the open formats.

I mean, so, like, to you and to all these people we're talking about, like, thank you.

Because I think this is kind of a big deal.

Like, this is.

This was like that moment, right?

This was the thing that, like, made us not suck.

It was.

It was really.

I mean, I.

I think we were.

We were a piece of a much larger group in the HUPO Protein Standards Initiative and Eric Deutsch.

And there was a lot of work to figure out what the standard should be, what should be in it, how to represent it, how to read it, how to write it.

And that was hundreds of people.

It was the whole community coming together and we were just really fortunate to be able to help support it as best we could.

And really glad it was a fun time to be part of because you did go from this moment where it was hard to have access to data to all of a sudden it being.

It being just there and a foundation that people expected.

Wow.

Okay.

I just want to say that.

Ben, your question.

I just want to show you the tablet that I knew the year.

Who knows.

And Prague.

I feel like I could almost.

Maybe it's a generalization, but I could basically guess how old you are.

Right.

Because I feel like they're.

It's a generational thing that open.

The open science thing.

And you know, and we run into it here, you know, the number of.

I can line up our faculty and say which ones are going to preprint and which ones are going to just automatically just assume that the data is going to go onto a public repository where it can be reanalyzed and the people that will not.

And, and I feel like, I don't know what, what's up with our generation that we're like hey, we should just share science.

I don't know if like, but like Carl said, element.

Yeah.

It's interesting to think of it as a movement that needed to happen, but it was.

There were people talking about hey, we need to deposit data.

We have examples going way back, things like GenBank that go back to the 70s, I think.

And then we saw the evolution of the PDB RCSB and how much came out of that, how that catalyzed the structural genomics efforts and the structure prediction efforts and Swiss Prot Uniprot of course as huge.

But there was a transition where it wasn't just data from large publicly funded projects, Human Genome Project, it was hey, I did a thing in my lab and there's leverage from other people being able to grab that and reanalyze it and mix it with their own data.

And I really believe that that is we spend so much time and effort collecting this data and making sure it's beautiful and there's so much more we can get out of it.

And but, but you're right, that wasn't always the perspective.

In part because it was hard.

It was hard, it was effort.

It wasn't clear how to do it.

Yeah, no, absolutely.

And it's big.

Where do you put it when you're done with it?

So honestly I felt like this conversation when he asked what you were going to talk about was going to go one of two ways.

It was either going to go here or it was going to go to Nautilus.

Right.

And I think that maybe some of the attention on social media for winning the award is that, oh wait, wait, is this a sign that where proteomics is going next gen.

Right.

And that's normally what you're talking about right now.

How to say, yeah, it is.

So I think a lot of people sort of take Proteo wizard and open things for granted.

They might not even know that it's associated with my lab or came out.

Of my lab raising my hand right here.

I'm even on weekly phone calls with them because of Psi Oblivious.

Keep going.

No, last year it was down downloaded 65,000 times and but now around 800.

Of those were me losing it.

I have no doubt.

Where did I put that?

And, and so I, I think, I think you're right.

I think a lot of people, you know, I've been in the community for a long time, but I've really been a supporter and a champion.

I'm trying to help proteomics just as a field.

And so I think people aren't always aware of how you've contributed.

And that's great.

That's what you want.

You want to be able to be helpful and supportive of a field.

And so certainly I think what Nautilus is doing is really exciting and I think it's going to be incredibly complementary to what we're doing with mass spectrometry in proteomics.

And I wear both hats and I love both hats.

And for people who aren't familiar, there's a lot of emerging proteomics technologies.

Nautilus is so.

Nautilus is a single molecule based protein quantification platform.

It works with intact or non digested proteins and the way it works to measure proteins is completely different than standard mass spectrometry based approaches.

It looks a lot more like DNA sequencing.

It has an optical readout instead of a mass spectrometric readout.

And ultimately we anticipate that it should have our platform anyway, is was designed for incredible scale, measuring billions of individual molecules so that you really could match the scale of the proteome and do it one molecule at a time.

Okay, well, I didn't know how much we were supposed to talk about that, but I did want to touch on that because there's just, you know, it's, it's an exciting time to be us.

Right?

There's lots of emerging technologies and it's like, okay, which one was this one again?

No, I think there very differentiated from each other and I, I personally very much view them as complementary in the same way that, you know, Kumasi gels and silver stained gels exist together.

You know, the western didn't, didn't, you know, kill the eliza.

They're, they're just different depending on the question you want to ask.

You pick the right tool to ask that question.

And so I'm excited that we're entering a phase where we have new emerging technologies where on one side we have things like fames really coming to the forefront and then on the other hand we have these spatial platforms and then we have the single molecule based platforms and sequencing platforms.

And it's a pretty neat renaissance, I think for proteomics.

Yeah, it's a good time.

Should be fun.

Yeah, absolutely.

I mean, to my mind, this is really a third wave in a way that we had that sort of very first wave where mass spec based proteomics was coming to the forefront.

You had things like the LCQ for folks who remember it, and then you had the wave where you had the really fast, you know, the Orbitrap FT slash, the really fast tofs coming to the forefront.

And I think this is a third wave that we're seeing and you know, things like the Tim Stoff and Astral and these single molecule methods.

Cool.

Okay.

I feel like I could totally talk about, I mean, even going back to the other stuff, like the whole time.

But this is the part where we like to switch over to kind of your origin story.

And I know the story of Proteo wizard and all these things is probably part of you, but more like the story of Park.

Like you.

How did you get here?

You can go back.

You can go back to your six and you got mad because somebody handed you one thing in one language and one in another and you're like, no, Universal.

I'm joking.

I don't know what that would be.

But tell it as you wish.

Go back as far as you want.

How'd you get here?

Well, I got here because I wanted to be an astronaut.

So my wife.

Wait, hold on.

That's, that's.

I get that my wife still applied to astronaut.

Like she was the last applying person, so that I chuckled.

But I know you go for it.

Yeah.

And I, as recently as the, you know, not the round that happened just now, but the round before that, I did apply to the astronaut training program and, and did reasonably well, but ultimately wasn't selected, which was a bummer.

So there are many people who, when they're, they're five, like, I want to be an astronaut.

And then by the time they're five and a half, they've moved on to being a fireman or, you know, a cowboy.

And, and my.

I was really serious about it.

And I love space.

I love the concept of being an astronaut.

I loved all of the aspects of the job, the teaching, the sharing science with the world.

And so in.

So, yes, as an elementary schooler, I loved space.

In high school, I went to space.

Camp or, oh, wait, like the one in North Alabama?

The one in Alabama, in Huntsville, Alabama.

I went to that one.

Was it before or after the movie?

I don't know the answer to that.

Okay, well, the movie made it popular.

What movie?

Osborne Space Camp.

Go watch it.

You should know this.

There is a movie, I'm just not sure when it came out because I was going to Space Camp.

It was a dream to go to Space Camp.

Absolutely.

So to be clear, I did technically go to Space Academy level two, which is the fourth.

So Space Camp is for middle schoolers.

Academy level one.

Yes.

And so, and, and it was, it was a thing where it was expensive and we couldn't really afford it.

So I actually worked summer jobs at the county fair and other places to be able to pay to go to Space Camp.

And, and it was this amazing transformative experience.

And while I was there, one of our counselors was talking about, about space flight and missions to Mars.

And that was my life plan as I was supposed to go to be on the mission to Mars.

Unfortunately, the mission to Mars hasn't happened yet, so I had to come up with a backup plan.

And so one of the, one of the counselors was talking about long term space flight and the calcium cycle and degradation.

And they mentioned that you couldn't just, it was hard to regulate.

And so what we really needed were designer proteins with new structures that could be really specific.

And, and so who is this counselor?

I really wish I knew.

My counselor.

I really wish I knew.

But they, they changed my life.

They, they're like, you should go study protein structure function.

And, and at the same time I had an amazing high school teacher who came from a molecular biology company and amazing computer science math teacher.

So all through high school I was getting lots of, I was excited about biology, biochemistry, I was excited about computing.

And then I was thinking about space and protein folding.

And as every high school student does.

Anyway, you went to a much better school district than me.

Where is this, is this California?

I was, I was, it was really, I was super lucky.

I was super lucky.

And, and so then in college, I, I, I already was.

I, I was faced with a choice actually.

So I went and, and chatted, was looking for an undergrad research opportunity.

And, and I remember I was, I was chatting with some folks, this is at Wash U.

And they're like, well, do you want to be on the DNA side or the protein side?

And I'm a freshman in college, what do I know?

But I said, proteins seem like they do all the work.

I want to be on the protein side.

I think that choice, that one sentence choice to a potential undergrad research advisor was how I ended up becoming a protein person.

Which could Random counselor in like north Alabama.

Yes, like exactly, yeah.

And so I started studying protein structure and as an Undergrad I actually had two totally separate projects as undergraduate research theses.

One was, was studying the International Space Station and it was a computer science project about, about remote sensing because you had this problem at the time that there were all these systems on board the ISS and you didn't have the bandwidth to get all of that sensor data of just is this, is it working?

Is it functioning back down to earth?

So how do you know that the ISS isn't malfunctioning when you actually don't have, you know, it was like a 7,600 baud modem was the amount of data you could transfer from ISS to ground.

And, and so how do you figure out if the ISS is working if you actually can't monitor all the systems all the time?

And, and so that was one of my research projects and the other one was in protein structure.

And as it turns out, both of them were really important because that problem of how do I figure out if something is working or not working without being able to sample all of it?

As it turns out, that is actually the biomarker discovery diagnostics problem.

So we were doing, we were doing diagnostics on the International Space Station, which was awesome.

And then my other life was doing protein structure prediction with Jay Ponder.

So yeah.

And then from there what was my.

I had a chemistry teacher who said, hey, I asked him, I'm thinking about going to grad school and where should I go?

And he wrote down a list of five names and I still have that yellow piece of paper with those names on it.

And one of them was David Eisenberg.

These folks are nice and they do great science.

I was like, okay, super.

So I applied to those schools, met with Dr.

Eisenberg, just loved, loved, loved, loved him and his lab and what he was studying.

And it was at that time of really thinking about large scale protein structure function studies and trying to predict protein structures for whole proteomes.

And it was also about that same time that mass spec proteomics was really coming about.

And Rudy and Matthias Both came to UCLA to give a seminar.

And I had asked Dr.

Eisenberg, hey, who should I think about doing a postdoc with?

And he said, well, these folks are both great, they're going to be here in a few months, you should chat with them.

And was again just really fortunate to be able to join Rudy's lab at a really pivotal time in the field.

That's pretty much how I got here.

That's.

So it all started with, as you said, a camp counselor in Alabama Wow.

I just, I mean again, I don't want to like put my story on yours, but like I remember that I had to save up for like two years.

It's like 600.

I remember that was like.

And then I went, but my counselor didn't say, you know, it's all about these designer proteins.

Like I was, we were just read it.

I'm an 11 year old boy, like running around, do you know, like doing the GS.

But like you're in a different place and get this moment and you're like on this trajectory.

Yeah, I love it.

It was, it was so important.

And, and even when I was getting into proteomics and I was thinking about my next step after grad school, it was my sister really who was key.

She sent me, my sister's 11 years older than me and a surgeon and, and researcher and she sent me some of the early biomarker papers and said, hey, it looks like this is going to be amazing for clinical care.

And this was the early stuff that I now teach people not to do.

But still it was the concept that hey, you could really get a snapshot of a person by measuring a drop of blood in their whole proteome.

And, and that was, that was actually really important in me choosing to go into mass spec.

Proteomics was the concept that you could measure physiologic state and you could do it at multiple time points and you could, you could do it incredibly deeply.

And of course plasma proteomics is really hard, but I didn't know that then.

And, and if you think about it from the astronaut perspective, if you wanted to study the difference between astronauts in space over time versus people on the ground, how cool would it be to take their proteomes and see all of.

These changes in, in, in like in your, like, so that International Space Station analogy, you're taking like you're pre, Is it that you're appreciating that you don't know things like, like I'm envisioning again like inner space because now like we are our own space, but you can't tell it all.

That's right.

That's right.

You can't, you can't measure everything all at once.

And so you have to make inferences about what's happening on incomplete information.

And so this is a classic set of problems, remote sensing problems, where you can't, you have, you can't measure everything and you have to do it from far away.

So if you want to know what's happening in the liver you, you know, you can't go and look at every cell in the liver.

So how do you figure it out based on the minimal subset of information that you're able to get?

You kind of blow my brain on.

I've been doing this too long and I've never thought about like that.

All right.

In undergrad, is this computer science and chemistry or what were your majors?

Yeah, so I, I had a little bit of a wandering path.

I, I started off, for one day I was a bioengineering major and then I decided that I didn't really, that the program at Washu at the time didn't have enough bio or engineering.

So I became a biochemistry through the chem department and computer science major.

And then somewhere around there there was a math major that I was attempting to do, but I ran out of time and had to graduate.

So I didn't quite finish that one.

But yeah, so it was always this intersection of biochemistry and computer science.

Is that where you picked up the coding for?

Sure, yeah, absolutely.

And really I think that thought process of thinking about algorithms and complexity and I actually think that that, that view that I gained in my undergraduate research project around information theory and information transfer really affects the way that I look at our biomarker discovery challenges.

And so my computer communications classes where we were learning about the Internet and IPv6 and things like that actually really shape the way that I look at problems in general.

Mass spec problems, data problems, biomarker problems, cancer diagnostics problems.

That information theoretical lens, that signal transfer lens, I think applies very generally.

Okay.

As an associate professor and a co founder of a company big enough that we all know about it, you're busy a lot, but what are you doing when you're not in the lab, when your hobbies, etc.

I might have one or two hobbies or professions, as the case may be.

So I've always been a person who believes in getting as much into life as you can.

And so alongside my life as a professor and as a founder, I've actually also worked as a professional circus performer and magician.

Like what, what part of the circus?

What are we talking?

We're talking juggling, stilt walking, fire eating.

But like aerials, really?

No, so I'm mostly a ground performer.

I can do a little bit of fabric, but.

But I am dominantly a ground performer.

But.

But yeah, little bits of tumbling.

Wow.

Did you say fire?

I said fire eating.

Yep, fire eating.

Okay.

I mean I do also juggle torches and play with other fire tools, but let's say My.

What about like sword eating or is that kind of drifting more towards the other side?

No, no, I mean, that's Carney.

I mean, Carney and circus are second cousins.

Um, I don't actually do sword swallowing.

Well, I do it.

I do a cheap hack of a magic trick that looks like I'm doing a sword swallowing act, but it's really a gag.

That's.

I, I went to again, the, the third cousin is like, I just went to the cabaret show the other day and like, they were like incredible.

It was all like, you know, these silks and like one dude had like a ring that he was like going around in.

Amazing people.

I love, I love the circus and magic communities.

They're filled with these just really talented, creative, very intentional, very detail oriented and also artistic people.

It's so much fun.

And yeah, so that's, I'd say that's my largest hobby.

I've had other hobbies.

I used to be a spin instructor.

I worked as part of a pop up restaurant for a while.

I mean, there's so much cool stuff in the world.

Okay, how does one get trained in circus performance?

So it started off, I guess, two journeys.

So first was as a kid I dorked around, which is normal, but I was terrible, utterly terrible.

In college, my roommate used to juggle in Renaissance fairs and was really active.

So we started a student group called Students Against Gravity.

We failed, but we tried very hard and so we would juggle all over campus.

And then when I moved to LA for grad school, there's a place in Los Angeles called the Magic Castle, which is a magician's guild, really special.

If you're ever in la, let me know.

It's members only, or you can get in if you're invited by a member and they have classes there that you can take.

And so I, for passing my quals, I promised myself that I would sign up for magic lessons there.

And that really took me to another level of taking this very seriously.

And yeah, and it sort of started off that I, you know, over time you get pretty good, you work on your own.

And then these are both.

Circus and magic are trades.

So you apprentice yourself to someone and you often have to audition to have someone take you on and be your mentor.

And so in my postdoc in la, I took on magic mentors, different mentors, and then auditioned in Seattle to have a mentor and was very fortunate to get one.

And so then over time, you start to, you start to get better.

You start to get better.

People are like, oh, hey, I have a.

I have a thing.

Can you, like, come and, you know, juggle for a minute?

And then over time, they're like, oh, you know, I have a club opening.

And so would you juggle in our nightclub?

Sure.

And then you start to have these experiences and you face a choice where, like, okay, I could stay a really good amateur, or I could kick it up a notch and become an exceedingly bad professional.

And the things that you need to learn at that point are not about the tricks.

They're not about technical skills.

They're about presentation and performance and movement and character and improv.

And so took a lot of classes like that and then.

Yeah, and I think so.

It was a combination of having really great mentors, just like we do in science.

And there are schools.

There's the circus school in Seattle.

Senka.

There's a great one in Los Angeles.

Tallahassee.

Yeah, Tallahassee.

Big one.

Tallahassee in Canada.

So there are places that you can go for didactic training.

The San Francisco School of Circus Arts is one of the better ones.

I went there in.

In college as well.

And so it was.

It was this parallel journey where I had science going on and circus magic going on.

I love it.

You know, again, back to the show.

I just saw, like, this person was like, she trained for four years to learn this art of, like, basically she hung from her hair.

Oh.

It was like she went to, like, Eastern Europe and, like, trained for four years, and she's still training.

I'm like, oh, my God.

So.

So you have this moment.

You're like, well, I'm revolutionizing the field of proteomics, but.

But maybe I should go to, like, Budapest and, like, like, get really good.

You.

Absolutely.

It is.

It is a commitment you'll hear about.

So, for instance, when you're working on.

On balancing something on your nose, which is a totally ridiculous thing to do, and you look silly doing it.

But the people who are really good at it, they.

There's a training program that starts with, like, a feather and then works your way down to, like, a spoon.

And the moment of inertia of a spoon is really small relative to a light feather.

But there's a program that you work on and handstands.

People will sit there for 20 minutes staring at a spot in the ground to really work on perfecting their handstands for hand balancing acts and things.

Wow.

Okay.

No, not what I was expecting you to say.

Um, but.

But I think that what we do find a lot of interesting hobbies and scientists as we're going through things.

And I think it's just maybe.

I think.

Well, I think there's a narrative that, that scientists are this really narrow thing.

And.

But the reality is scientists are people, and it's just one of our many dimensions.

We're allowed to be circus performers.

We're allowed to be chefs.

We're allowed to, you know, go out on week, on weekends and look at the flowers or those are the.

We are, as it turns out, humans.

And we exist around a distribution.

And we've found.

I mean, it is, you know, like, everyone needs that other outlet.

I mean, I do think science is way more creative than people outside of science probably realize.

But you do have.

I mean, we've had a lot of climbers, multiple ceramics, I'm sure some artists, you know, like, it's.

It's a thing, you know, definitely bakers.

You're 100% the first, you know, circus magic person.

But do you.

But is it still that kind of, like, it's.

Is it itching that other itch or is it providing that release?

You know, like, I mean, I guess that's kind of the other question.

Like, sometimes, I mean, I love my job, but I kind of hate my job, if that makes sense.

And so then, like, my hobby would be the thing I kind of need to be doing instead.

But.

But then sometimes it's a release.

Like, is it kind of all those to you or both?

You know, I think, I think it.

I guess it's, it's.

It's all of those things.

I think when I would have a really hard problem.

Rudy remembers this because he used to laugh at me.

And when I.

When I couldn't figure it out, I would go down to the, to the park near Skatsworth's park and just like juggle for an hour.

And.

And then I wasn't necessarily thinking about the problem directly, but there was something about it that was very meditative and there was a background process happening and, And I would come back and I had to figure it out.

And so it helped my science as well.

So I think it's.

I do think it is tempting to get locked into a box and be like, I am a scientist, I am one dimensional.

But I.

And there are people who.

Their entire world.

And that's great if that's how they're most productive and how they're most fulfilled.

For me, I love diversity.

I love.

I love tapas when we go out to eat, because I get to try lots of little things.

And so for me, I just, I've Always appreciated how all the different elements of things come together and they shape your perspective.

The fact that I went to space camp when I was in high school shapes my perspective of how I do my science.

And I think that diversity enriches our entire community because we can be approaching the same problem, but all of our history is going to impact how we're going to go about it, how we're going to interpret it, how we're going to interpret what we see.

And so really enriches the entire approach to science because it's so.

I just think it's essential.

Yeah.

Yeah.

Okay.

Well, again, we could probably talk about this for another hour, but we have to.

Again.

So a slight thing that we do for this one specifically is we ask people if they know anything about Portland, would they recommend something about Portland?

Have you ever been to Portland?

I've been to Portland.

We have great collaborators at ohsu.

One of my close friends from the Aversal Lab, Mark Flory, lives in Portland.

Oh, he's going to be on the show at some point.

He's amazing.

Ask him about kite surfing as well.

What I would say about Portland.

I'm going to go a slightly food direction with Portland.

Really exceptional place to get liege waffles.

So if you're not familiar, I only know that name from my cycling race, so what the heck is that?

There are different types of waffles, and this is a subclass of waffles that they're a little sweeter, you typically don't need to put syrup on them.

And they are delicious and slightly caramelized, crispy.

Where do I get them?

Like, is it just a thing like Portland?

There are lots of cool waffle waffle places around Portland.

Did you say liege?

Like the, like Belgium?

Like liege.

Okay, so it is like the cyclomes.

Okay, cool.

Sorry.

Anyone listening hates me.

Okay, cool.

Thank you.

That's a great suggestion.

I love it.

But just remember that they are already sweet to begin with, so do not immediately douse them in syrup or else they might be a little too sweet after that.

Even if you're from the south, if.

You'Re in the south, then please feel free to douse them in syrup.

Yeah, you need a lot of syrup.

Come on, guys.

I'm not saying.

I'm not saying it.

You know, they will be bad doused in syrup.

I'm just saying, depending on your personal sugar tastes, you may want to.

Now, Ben, Natalie took me to a Waffle House in South Carolina the first time we hung out.

So as you should Imagine there might be some syrup involved.

Just, just go straight to the K wrap.

Like, don't even pretend it's syrup.

Do you ever.

You don't like the K wraps?

Oh, yeah.

Okay, so, so the way, way we've been wrapping this, this season up is, is by asking what are you most excited about in terms of where proteomics is going?

What are the developments and the directions that motivate you?

Well, I, I have always believed that proteomics should not, should, should just be how people do science.

I mean, proteins do everything.

They make, they make us go.

And so I am excited about seeing proteomics leave the proteomics community and just be the way that biologists do science.

And I think we're seeing more and more appreciation for the value of the proteome throughout the world and I think our tools are getting more powerful.

I do think the single molecule methods are going to be incredibly powerful.

And also.

So I think anything we can do to reduce the barrier to everyone in the world saying like, oh yeah, go get the proteome, that's where we need to be.

Wow, that, that's really well said.

And okay, so, so if you go back to your freshman year and you had said DNA, do you think that you would have the same perspective?

Right.

How much of that is the, the influence of your path there right at that fork?

So I think.

So I was at AHSG recently and had a really interesting experience chatting with a number of geneticists.

And you know, I would, I would call myself many things, cancer biologist, biochemist, et cetera.

But, but I actually, and I think a lot about multi omic integration, but I always think about it in terms of function.

And, and so it was really interesting at this meeting where you talk to people and be like, okay, well, so how do you think that snp, that variation, that GWAS thing that you observed, what happens to it?

How does it actually lead to the phenotype that you're seeing?

And more often than not, the answer I got was, well, that's really complicated.

And I don't know how to, I don't know how to look at that.

And I was surprised.

It was almost like studying the proteome was this daunting, overwhelming.

There was just a barrier because it was so complicated.

And it is complicated.

I mean, proteins are complicated, but they also.

So I could imagine if I had said DNA, I might be in the camp of, wow, that's complicated.

As opposed to in the camp of you have to have this information.

Impossible to say.

Right?

But, yeah, but you know, I feel.

Like also be a professional circus performer and have left science entirely or in five years.

He's on an ass.

He's on a rocket.

Yeah.

Yeah.

Okay.

This.

This was a lot of fun, Prague, but I think we're.

We're running up on time, so I think I have to thank.

Absolutely.

Looking forward to your talk in Portland and looking forward to meeting you again.

We passed an elevator in Mexico.

You had a fantastic suit on.

I'm very jealous.

I like to be sparkly.

Just distracts people from the bad signs.

No.

Thank you so much.

This has been really fun today, and it was really great chatting with you both.

Yeah, thanks.

So this is part where we do the credits.

The Views Express are solely ours and not our employers.

We want to thank us, Hupo, for sponsoring this series.

We want to thank Johannes for the intro and exit song, Kaylee Kirkwood for our artwork.

And you can email us and we're gonna read them on the air.

But write theprodium@showmail.com, please, like, subscribe, give thumbs up, and.

Yeah, keep listening wherever you listen.

Thanks.

By.