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$4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

arstechnica.com

11–20 of 37 posts

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#11
I was in the audience at the NY AWS summit ... quite a loud applause when they give their per hour cost number. I was also impressed. However, I found it a bit surprising that that it took 2 hours to acquire the VMs, and 1 hour to do the actual work.

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#12
post #9

While it's nice from a technical perspective, this is unlikely to lead to a cancer cure. Having worked in cancer drug development, I can tell you, there is no shortage of cancer targets. Researchers have a list of targets they want to hit, and chemists are pretty darn good at designing small molecule compounds to hit them. The problem in cancer is not that we don't understand individual proteins or the way that drugs…

(Bioinformatician here). Although I think bench work is the most obvious route and the most likely way these problems will be solved, there are in principle some computational ways they could be addressed.

If we had good computational models of how perturbations would affect transcription networks, for example, we could predict these "side pathways" that so often occur in humans but not in mice.

But you're right, the reality is complex, and you have do deal not only with transcription, but translation, post-translational modification, non-coding RNAs, the list goes on... And most current models of this type don't delve into 3D simulation. Some people are working on whole-cell modeling but that's in its infancy.

Ultimately I believe the breakthroughs will come fastest if we can "close the feedback loop" by automating a lot of bench biology, and then have computers both generate and test hypotheses.

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#13

> As impressive as it sounds, such a cluster can be spun up by anyone with the proper expertise, without talking to a single employee of Amazon. This isn't actually true. There's initially an instance limit of 20, and you have to contact Amazon to get it lifted. You could probably order just as many servers at Softlayer or purchase them at Dell without talking to anyone (except the guy who confirms your credit card).…

Bump ... I've had personal experience where I needed a few 100 VMs for a short experiment. A quick message to Amazon got the job done. Took less than a day to get approval.

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#14
post #11

I was in the audience at the NY AWS summit ... quite a loud applause when they give their per hour cost number. I was also impressed. However, I found it a bit surprising that that it took 2 hours to acquire the VMs, and 1 hour to do the actual work.

I was there as well. Pretty cool stuff!

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#15
post #9

While it's nice from a technical perspective, this is unlikely to lead to a cancer cure. Having worked in cancer drug development, I can tell you, there is no shortage of cancer targets. Researchers have a list of targets they want to hit, and chemists are pretty darn good at designing small molecule compounds to hit them. The problem in cancer is not that we don't understand individual proteins or the way that drugs…

I agree mostly with your post but there are computational approaches being developed that may help improve our understanding of these cancer networks. They will in no way eliminates or reduce the need for wet lab biology but hopefully it will couple with improvements in high throughput experimental technology to help us design and make sense of experiments targeted at understanding the whole phenomena.

I work on computational approaches to using known, wet-bench validated interactions along with high-throughput cancer data, and agree that much more high-throughput data is needed, more so than small-scale approaches. Quantitative measurements of interactions rates in vitro are no more trustworthy than computational methods on high-throughput data, because you never know what other cofactors may be affecting the interaction, or what compartmentalization or localization you missed in your model system that's different in a real system.

I see the only scientifically defensible way forward is to do large, data-rich networks like Eric Schadt does them. Individual wet-bench work is good to use as prior data, but it's just a hint at a part of a large, complex system, and overly reductive approaches are going to completely miss the big picture.

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#16

Earlier quoted context omitted.

I agree mostly with your post but there are computational approaches being developed that may help improve our understanding of these cancer networks. They will in no way eliminates or reduce the need for wet lab biology but hopefully it will couple with improvements in high throughput experimental technology to help us design and make sense of experiments targeted at understanding the whole phenomena.

I work on computational approaches to using known, wet-bench validated interactions along with high-throughput cancer data, and agree that much more high-throughput data is needed, more so than small-scale approaches. Quantitative measurements of interactions rates in vitro are no more trustworthy than computational methods on high-throughput data, because you never know what other cofactors may be affecting the inte…

Unfortunately, for non-computational peers and reviewers, "high-throughput" is often a synonym for "fishing expedition". This perception is gradually changing, though.

Furthermore high-throughput assays are more expensive so people often cut corners on sample size.

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#19
post #12
post #9

While it's nice from a technical perspective, this is unlikely to lead to a cancer cure. Having worked in cancer drug development, I can tell you, there is no shortage of cancer targets. Researchers have a list of targets they want to hit, and chemists are pretty darn good at designing small molecule compounds to hit them. The problem in cancer is not that we don't understand individual proteins or the way that drugs…

(Bioinformatician here). Although I think bench work is the most obvious route and the most likely way these problems will be solved, there are in principle some computational ways they could be addressed. If we had good computational models of how perturbations would affect transcription networks, for example, we could predict these "side pathways" that so often occur in humans but not in mice. But you're right, the…

(former bioinformatician here)

I agree, the totality of the interactions for a single cell is so many orders of magnitude above what we are capable of currently modeling that I fear these computational approaches are dangerously over-hyped. Having been privy to the state-of-the-art projects in a lab with a ~5,000 node cluster it was still disappointing to see how rough the whole cell modeling approaches were. It's really tough just to model a small corner of the cytoplasm and get the diffusion of different protein and metabolites right, let alone address organelles or chromosomal folding and surface availability. It's a mess.

Re: $4,829-per-hour supercomputer built on Amazon cloud to fuel cancer research

#20

In what programming language would this cross-CPU simulation software be built?

The actual application used was Glide, http://www.schrodinger.com/products/14/5/, which is likely Fortran or C++ given the type of app. Don't know what Cycle's core sofware for managing the whole infrastructure is written in, but they use a lot of Chef and schedulers like Torque or Condor in addition to Boto to orchestrate the EC2 side.
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