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Heroku for Science

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Re: Heroku for Science

#21

Post by skosuri »

irollboozers wrote: post #13
skosuri wrote: post #9

In our lab today we are consistently dealing with the opposite problem. The experiments themselves are easy in comparison with the design and analysis.

The startup equivalent would be "it's easy to build the app, it's hard to get users". Not all apps can yield users, but lowering the bar to launch will certainly yield more opportunities for successful apps.

You are right. I think we would all appreciate making more stuff that we do automatable and outsourceable. I guess where I was trying to go with the comment is that it would be nice if there were similar tools for design and analysis. Oh automated paper writing would also be much appreciated.

Re: Heroku for Science

#22

Post by srunni »

alejoriveralara wrote: post #3

I believe this startup is as close as it gets (for now!) to what you're describing, https://www.transcriptic.com/ . (I don't work there or anything)

I'm a biomedical engineering graduate student at a research university. While I haven't investigated Transcriptic's pricing in depth, based on a conversation with one of their employees about collecting some basic growth curves (https://www.transcriptic.com/guides/3-growth-curves.html), their prices were simply far too high (even with the steep discount they offered) for repetitively collecting a large amount of data - precisely the situation in which you'd want to use something like Transcriptic. This is especially true for labs (such as mine) that have already made the upfront capital investment for the equipment used to take these measurements. As for the repetitive labor, you can usually find undergrads to do that for far less (often completely free) than what Transcriptic charges.

However, a service like Transcriptic may make sense if (a) you're in a company (no free undergrad labor, though summer interns may be a suitable alternative) or (b) you don't already have the equipment and just want to do a one-off collection of a large amount of data. Also, maybe prices will significantly drop as Transcriptic scales up and streamlines their operations. I'll definitely be checking back in the coming years to see if they ever reach the point where it makes sense to use their services.

Re: Heroku for Science

#23

Post by henryaj »

bignaj wrote: post #12
L_Rahman wrote: post #2

I studied biomedical engineering at Hopkins. Before I started there, research was the promised land. I dreamt of spending my time thinking about how to solve critical problems and testing solutions. What I saw instead were people spending the vast majority of their time pipetting. All the way up the ladder, upto and including postdocs. I sometimes thought our PI had it worse for having to spend most of her time apply…

I also thought research was the promised land. Went to Cornell for undergrad studying biological sciences and was amazed at the research opportunities... but then worked in a lab studying type II diabetes. I pipetted, cleaned beakers, measured out chemicals to prepare solutions, sucked up cell cultures and extracted DNA all day making $8/hour in extreme boredom. There were postdocs with Ph.Ds and loads of experience…

So depressing. This (and the parent comment) is the reason I didn't go into research -- it's a life of pipetting and manual labour that no-one's interested in automating, either because it's too complex or because labour is so cheap that there's no financial incentive to do so.

I'm happy to leave someone else to do that. I'd rather be in a job I actually enjoy the day-to-day of.

And that's to say nothing of the problems of PhDs: namely that there are ten times more PhD positions than there are postdoc positions. That ten-to-one crunch when it comes to finding a job sure does sound fun...

Re: Heroku for Science

#24

Post by ejstronge »

henryaj wrote: post #23
bignaj wrote: post #12

Earlier quoted context omitted.

I also thought research was the promised land. Went to Cornell for undergrad studying biological sciences and was amazed at the research opportunities... but then worked in a lab studying type II diabetes. I pipetted, cleaned beakers, measured out chemicals to prepare solutions, sucked up cell cultures and extracted DNA all day making $8/hour in extreme boredom. There were postdocs with Ph.Ds and loads of experience…

So depressing. This (and the parent comment) is the reason I didn't go into research -- it's a life of pipetting and manual labour that no-one's interested in automating, either because it's too complex or because labour is so cheap that there's no financial incentive to do so. I'm happy to leave someone else to do that. I'd rather be in a job I actually enjoy the day-to-day of. And that's to say nothing of the probl…

With the utmost respect to you and the post you responded to, research is about answering questions to things you find interesting; for a biologist, pipetting is simply the means you take to get there.

If you want to contribute to Firefox or any other non-trivial open source project, you need to spend time creating a development environment and it likely will take weeks to months before you can make a substantive contribution.

If anyone is reading the comment I'm responding to or its parent comment, keep in mind that the manual labor is in pursuit of a goal.

Re: Heroku for Science

#25

Post by bbgm »

Most worthwhile research is about the mundane. One of the first research projects I did required painstakingly adjusting and modifying conditions to the point that I could actually start collecting data. That process took weeks, but the day it worked was insanely satisfying. In the process I became a master at making small incremental changes, recording them, and learning exactly what didn't work. Years later, as a computational scientist, the process was much the same, except that there were no pipettes and beakers involved.

Any worthwhile work I have ever done has mostly been about grunt work. Along the way there have been cool things (after all Leno made fun of our research [1] once) and insanely fun times. I may not be in research now, but every day I apply the lessons learned from patiently repeating and iterating.

1. http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=723226...

Re: Heroku for Science

#26

Post by innguest »

ejstronge wrote: post #24
henryaj wrote: post #23

Earlier quoted context omitted.

So depressing. This (and the parent comment) is the reason I didn't go into research -- it's a life of pipetting and manual labour that no-one's interested in automating, either because it's too complex or because labour is so cheap that there's no financial incentive to do so. I'm happy to leave someone else to do that. I'd rather be in a job I actually enjoy the day-to-day of. And that's to say nothing of the probl…

With the utmost respect to you and the post you responded to, research is about answering questions to things you find interesting; for a biologist, pipetting is simply the means you take to get there. If you want to contribute to Firefox or any other non-trivial open source project, you need to spend time creating a development environment and it likely will take weeks to months before you can make a substantive con…

I think your parent is alluding to the fact things could be automated in biological research but aren't because of the disincentives; and that at the same time things in tech are more amenable to automation and often parts of it are indeed automated.

Yes, it's all a means to an end, but how much time one wants to spend in the "means" (which can get extremely repetitive, apparently) is what counts for the parent (I'm supposing).

Re: Heroku for Science

#27

Post by cing »

aheilbut wrote: post #18

The problem with this fantasy is that easily automated and distributed tasks are not the rate-limiting steps in most biomedical research. The hard parts (in addition to designing the right experiments and analyzing data..) are in constructing and validating relevant model systems and doing the specific experiments to address questions of interest. These are extremely dependent on the question being studied and often…

This is certainly the bottleneck in my research. I ran thousands of core years of computer simulation in the first year of my PhD. I have all the data I need to write a PhD thesis but I'm still years from graduating due to the aforementioned bottlenecks. An arsenal of software I've written in numpy/scipy/pandas saves time, but only goes so far when you're trying to carve out stories from your data to write papers.

Re: Heroku for Science

#28

Post by stanzheng »

The Center for Open Science poses itself as something similar to what you describe. http://centerforopenscience.org/

I believe they call themselves more of the Github of Science for scientific collaboration. Adding hooks to 'push' the tasks and 'checkout' the findings could be maybe extensible on their platform.

Re: Heroku for Science

#29

Post by cagenut »

frisco wrote: post #10
alejoriveralara wrote: post #3

I believe this startup is as close as it gets (for now!) to what you're describing, https://www.transcriptic.com/ . (I don't work there or anything)

Hey! Founder of Transcriptic here. This is exactly what we are. We're growing quickly and have customers at over a dozen academic institutions now. One of our key issues right now is that biologists aren't programmers and so we're doing a lot of hand-holding - we'd get really excited about someone building higher level tools (Heroku to our AWS) on top of us for specific domains that you know better than we do. If any…

Hi Max, I took a look at your jobs page and my heart sank at this: https://jobs.lever.co/transcriptic/e1cfcb93-05d8-4026-8f70-3...

The first two bullet points there are like the two biggest red flags possible in an ops job post. It reads as a development team that has built a fragile and unreliable system and is looking for a superman to dump it on.

It will matter much more if your VP of Engineering position can capacity plan than it will matter if your operations position can code. No amount of ops rockstars can fight a (larger) dev team that won't design with real world workload capacity and reliability as not just a concern but a focus.

Re: Heroku for Science

#30

Post by yeukhon »

From my experience (having done a similar project as an undergrad) is that the first problem is convincing people to switch and take the risk/time to use your new workflow, even if your workflow allows them to continue to use their existing infrastructure / machines.
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