73 replies to this topic

[Brainbox]

After that we need to know how to restore data and we need to know what data needs to be restored or will soon need to be restored.

But before we can do that we need a model. If we want to do more with it than just storage and retrieval, we would need a semantic model.

Creation of a semantic model is the reason for my somewhat unprofessional and naive (in the context of biotech) post above. But give me the benefit of the doubt for some time....

[maestro949]

As far as my understanding of biology goes, the analogy with systems (software) engineering is only partially applicable.

This is true for several reasons. Biology is a computational system based on information but it differs in that:

1. The state data and logic (the software code) are both mutable in biology. In typical software development the code is fairly static. Biological systems are adaptive to their environment to a degree.
2. Software is usually developed to follow a strict set of rules whereas biology (with the exception of development biology) runs on chaos / statistical principals
3. The majority of the computational function in biology is carried out in a 3D Cartesian space where enzymes and proteins are bumping into each other. In a computing system it reduces to a binary set of binary data and if/then statements.

Theres an impedance mismatch between the two which is one of the reasons it's why it's difficult to map biological function to software function. Imagine your data in memory, code, database schema and hardware all changing to adapt to it's environment. That's not easy to simulate and where it is done, it's computationally expensive requiring lots of computing horsepower.

Another major challenge is that biology works on many scales and across those scales simultaneously :

Sub Atomic (Proton Pumps, Electron transport)
Atomic (Metabolism)
Molecular (Metabolism, Signaling)
Proteins (DNA, RNA & Function)
Protein Complexes (Structure, Function)
Subcellular Components (mitos, ribosome, etc)
Cells
Tissues
Organs
Organ Systems

And at many different speeds:

femtosecond
picosecond
nanosecond
microsecond
millisecond
centisecond
second
minute

The more scales and speeds you cross, the more difficult it becomes to model biology.

Where to start? How to reduce the ridiculous complexity?

Here's an excellent writeup regarding the inherent challenges to systems biology from the Institute For Systems Biology that details the inherent challenges.

[eternaltraveler]

meastro,

What, if any, interventions do you propose, or are you saying that only by investing in systems biology will we know what to target and how to target it? Fixing aging through metabolism (ie fixing the repair mechanisms infinitely well so they both completely halt the accumulation of damage, and remain undamaged themselves), would require rewriting of the genetic code in ways never before conceived of by evolution. Humans already are one of the longest lived mammals (and animals). There has never been any drive for evolution to come up with answers to deal with slowly accumulating forms of damage that would result in death well after death from extrinsic causes would have occurred. Until recently that is, death from aging actually becoming a common thing in industrialized nations.

This itself is incredibly daunting, but even if accomplished doesn't provide answers on how to deliver these fundamental interventions to adult humans (molecular nanotechnology?). Though if it were accomplished it would provide information on how to fix our progeny, which means at least generations to come might not have to deal with the scourge we do.

Perhaps I don't have as firm a grasp as you do on systems biology and how it reasonably could provide answers/interventions in a reasonable timeframe. Perhaps somewhat because "systems biology" itself is rather vaguely defined, other than it being integrative rather than reductionist (mostly because we aren’t smart enough to be all that integrative, and computers can’t even fold proteins reliably yet, let alone model their behavior in the environment). Could you explain exactly what you think what the first several steps would be under this model, and how they might reasonably be accomplished? (i realize that might be asking a lot, as it's much harder than what I have to do as I only have to point you to SENS and say I mostly agree with it, even if there are a few instances where I differ somewhat) but I'd like to understand exactly what you think is the best course, and why (though I think you’ve explained a lot of your position’s “why” but not so much of the course).

cheers

[eternaltraveler]

So are you planning to sequence your genetic information for inclusion in a database where it can be stored digitally then backed up to DDS-5 and archive quality optical discs and kept in a dark room?

ummm... no?

Though I'd certainly sequence it if the price came down 2 orders of magnitude, but not for anything like the reasons you suggest.

[eternaltraveler]

Ouch. A $900 trillion cost if every person were to do this only once ($150k * 6b). Combine that with the risk of death, having to find a suitable donor and the 45 day hospital stay, this just isn't a practical solution, even at a fraction of the cost.

a. I'm not suggesting doing this tomorrow ). It would be ridiculous for reasons having nothing to do with the cost. It's a simple proof of concept that does work today, even with severe problems.

b. When those problems are solved it will still be expensive. Everyone on earth won't benefit initially from any new technology. Give it a 10-20 year gap between the richest and the poorest. Less if people get their priorites striaght as Aubrey hopes.

[Brainbox]

Another major challenge is that biology works on many scales and across those scales simultaneously

That's the reason to make a model step-by-step, using the structure imposed by the different aggregation levels of biological structures as a guideline. I will read the link you provided this evening. However, I think I have some knowledge already to propose, in coarse outline, a following approach. According the scale and consequently the costs, it will be huge. But it could do no harm to try to model a simple example as a try-out, eventually within imminst. I'm not impressed by initiatives that failed in the past, we should learn from them and make a next step forward.
IMO, the basis approach could be as follows:
- The basis would be a static semantic model that contains the relationships (or interfaces) between the different entities. This would be a highly experimental process. Start with a certain level of abstraction, then another (lower) level etc.
- Try to integrate (parts of) these models into one. Maybe not possible due to complexity.
- Only after that, start to try to model the dynamic behaviour of these structures. Based on a stepwise approach, function by function.
- Try to integrate the dynamic behavioural models. Once again, very difficult.

For the static semantic model I would suggest the NIAM methodology. I was not able to find an English reference for it on short notice. This modelling technique has both affinity with relational and object types of core modelling. For the dynamic models I don't have a clue yet as to what would be appropriate. I think several modelling techniques would apply, depending on the time domains (speeds). Edit: I think a petri-net would a moddeling technique highly appropriate to make a model of the general time domain dependencies.

Am I overenthusiastic and underestimating the issues one will encounter by such an initiative? Yes, definitly.
Should we stay put and sit on our hands because of that? I think not.

I would like to start a simple pilot, using a chapter from a biology textbook that describes the relation of e.g. amino acids and their function in the body, e.g. with maestro and one or two others, to get some feeling for it. Chances are we will get realy confused and need to stop to rethink.

What do you think? Could this grow into something that has any practical value? Am I thinking to simplistic?

Edited by brainbox, 08 August 2007 - 01:18 PM.

[maestro949]

meastro,

What, if any, interventions do you propose, or are you saying that only by investing in systems biology will we know what to target and how to target it?  Fixing aging through metabolism (ie fixing the repair mechanisms infinitely well so they both completely halt the accumulation of damage, and remain undamaged themselves), would require rewriting of the genetic code in ways never before conceived of by evolution. 

I propose we not focus on tweaking the genes themselves (unless they are truly broken) but rather the epigenomic and trascriptomic layers that sit right on top of it. To do this we need to have a fairly comprehensive understanding of which expression levels we can up or down regulate. I think that the gene expression loosens up as cells age leading to suboptimal performance across numerous proteomic functions. I see this as the key target of aging interventions as it is damage itself. In my opinion, this, combined with the gradual improvements already happening appear to be this generation's only hope. We still need stem cells to emerge and we still need cancer therapies to emerge. I'm assuming they will which is why I think it makes sense to look for a sure-bet upstream metabolic fix that slows the functional decline.

There's 3 seconds on the clock and we've got one hail mary pass to throw. To me, this is it.

Humans already are one of the longest lived mammals (and animals).  There has never been any drive for evolution to come up with answers to deal with slowly accumulating forms of damage that would result in death well after death from extrinsic causes would have occurred.  Until recently that is, death from aging actually becoming a common thing in industrialized nations.

Agreed. We'll still need to fix the damage too. We're going to need a few silver bullet fixes though that put a serious dent in the rate of aging if we want to be around long enough for each and every fix to reach a point of economic viability.

This itself is incredibly daunting...

Agreed. It wont be easy.

... but even if accomplished doesn't provide answers on how to deliver these fundamental interventions to adult humans (molecular nanotechnology?).

I argue that it will provide answers. We can modulate gene expression via RNAi techniques and tighten up this gene expression. By having a complete metablomic map we will know what gene expressions to tweak in order to restore cell function to a more optimal level. Having a more clear picture will also prevent us from introducing unwanted damage that many of the drugs and therapies we use today cause.

  Though if it were accomplished it would provide information on how to fix our progeny, which means at least generations to come might not have to deal with the scourge we do. 

I agree. If we don't accomplish our goals in time, lets leave something for future generations to build on. Any lack of confidence that it can happen should not affect our motivation or effort. The only certainty is that by doing nothing, we fail. Besides, they will no doubt have the computing horsepower to finish off the task. Even moore's law gets us very close in 20-30 years for doing real-time molecular dynamics. Many of us can hang around that long so prepping the next generation with the framework, tools and data is not a bad approach. The sooner we get going on the tools they need, even if it's just the designs and prototypes, the greater our chances for longevity.

Perhaps I don't have as firm a grasp as you do on systems biology and how it reasonably could provide answers/interventions in a reasonable timeframe. 

It's not so much a firm grasp but rather a gut feel after working on large-scale and complex software projects and working my way through much of the theoretical gerontology literature. There are many analogies between large and complex software projects and biological functions. I think the overlapping knowledge has lead me to these conclusions. I may be entirely wrong but it feels right.

Perhaps somewhat because "systems biology" itself is rather vaguely defined, other than it being integrative rather than reductionist (mostly because we aren’t smart enough to be all that integrative, and computers can’t even fold proteins reliably yet, let alone model their behavior in the environment).

This is all true. There's lot of blurriness and our ape minds are terrible at dealing with complexity. We lack much of the horsepower we would need to build a fully integrated and functional model so the early iterations of the systems tools that emerge would be left with some gaping holes and lots of inference. As more data and more horespower comes on line though we can simply fill in the gaps. The systems models and tools will evolve to match what we're capable of doing. My hope would be that once we got the ball rolling and demonstrated the value, a desire would emerge to flush this out as fast as possible in a similar fashion that the genome project accelerated as it went along.

  Could you explain exactly what you think what the first several steps would be under this model, and how they might reasonably be accomplished?

1. It starts with the -omics data. Collect it all and organize it all. Denormalize it and map it all it together.

2. Collect biomarker data and layer that on top of the above data. For aging, we need biomarkers. Lots of them and at all levels of the human systems. Aging is simply a process of change and nothing more. We need to identify where all of this change is taking place and understand it completely. What precisely is changing at 20, 30, 40, 50, 60, 70, 80, 90, 100...

3. Continuously Refine our data, models and test procedures such that changes (aging) can be detected as early as possible and "fixed" with whatever tools we have available.

Those are the most important step! Everything emerges from this. Statistical/predictive analysis, simulations, functional models, better tools and finally, specific and more elegant fixes that can be tested and implemented with relatively low cost via a series of personalized tweaks to keep homestasis stable.

(i realize that might be asking a lot, as it's much harder than what I have to do as I only have to point you to SENS and say I mostly agree with it, even if there are a few instances where I differ somewhat) but I'd like to understand exactly what you think is the best course, and why (though I think you’ve explained a lot of your position’s “why” but not so much of the course).

I like much of SENS and think that a good deal of the damage will still need repairs I just don't see it getting the critical mass and funding it needs in the necessary timeframes for us thus I want to continuously explore the full spectrum of options. The general public are like children that scream about going to the beach only to have a great time when they're there. We're going to have to drag them kicking and screaming I fear. Asking them to part with their money is futile. People dying of cancer hoard their money, elderly dump it into slot machines despite the fact that they are teetering on the edge of death. Bizarre.


Edit: Touch ups for clarification

Edited by maestro949, 08 August 2007 - 03:08 PM.

[caston]

ummm... no?

Though I'd certainly sequence it if the price came down 2 orders of magnitude, but not for anything like the reasons you suggest.

Well I don't know as much about biotechology as you do but I would. It baffles me why you do not want a digital backup of your genetic code for future rejuvenation therapies.

So if you had the option to sequence your own code what would you do with it to help you extend your lifespan?

Edited by caston, 08 August 2007 - 04:00 PM.

[maestro949]

a.  I'm not suggesting doing this tomorrow ).  It would be ridiculous for reasons having nothing to do with the cost.  It's a simple proof of concept that does work today, even with severe problems.

b.  When those problems are solved it will still be expensive.  Everyone on earth won't benefit initially from any new technology.  Give it a 10-20 year gap between the richest and the poorest.  Less if people get their priorites striaght as Aubrey hopes.

Understood. I fully agree that we'll be able to devise a fix for all damage regardless how unwieldy they are and that getting them into the market will allow market forces to drive costs down. I just think it's going to take more of a brute force attack on the complexity to solve many of the problems we can't get past today.

It's as if we chase lots of the biological goblin raiders into the forest of complexity and nobody wants to go in there to flush them out because nobody has yet to return. SENS proposes that we just keep rebuilding the village after each attack until help comes. Help isn't coming so I propose we study the goblins, form a party, go around the forest, find their food supplies and seize control of them. Then the goblins will be under our control. [tung]

[Luna]

SENS is the only chance for us to actually survive the next 100 years :X

And still, more people believe in ghosts than they do in SENS..!

Metabolism engineering will take.. forever.. (lucky we have sens).

[maestro949]

SENS is the only chance for us to actually survive the next 100 years :X

And still, more people believe in ghosts than they do in SENS..!

Metabolism engineering will take.. forever.. (lucky we have sens).

OK. I'm convinced. Ignore everything I wrote. [mellow]

[Traclo]

Elrond,
I'm wondering about the practical testing of the damage repair that you suggest. Considering that as maestro says there may be layers of damage (it's what I got out of it, perhaps not what was intended but it suffices to express my idea, apologies maestro if that isn't what you implied), and also considering the amount of things that we don't know about aging, what will be the application of the repairs be like?

It seems to me that once we repair all the damage that we are aware of and the cells seem fine, clinical trials and testing of this would take a lifetime to preform. And even at that point there may be things we have yet to find out about the damage presented by aging. So is our best solution really to repair the bridge when the truth may be that the foundation is eroding?

Or can we, as maestro suggests, first (not suggesting exclusive work on but rather primary focus on) discover the mechanisms and actual extent of the damage, before trying to fix it? Because if our knowledge is incomplete and there are other factors of which we are currently unaware, then a single one of these can doom us to failure, while we celebrate the triumph of fixing "all" the problems.

Perhaps I'm incorrect and our current knowledge of aging is sufficient to focus on fixing the problems apparent to us, but if you would not mind expanding on if our present information is truly enough, or if we should approach the problem as maestro suggests and really understand what we are fighting before primarily focusing on fixing it, it would be greatly appreciated.

Note: I'm not trying to sound depressing, or be a nay-sayer but problems such as these are very pertinent to the direction which we should be progressing...
Unless I'm completely wrong!

[Luna]

I could be wrong but.. in metabolism there isn't anything that should unknowingly kill us.
Actually, the problem, seems to me, is that metabolism (and other things in the body) are defective, which is why lifeforms age.

So since we are pretty sure we know all the damages that are caused to us, it should be enough.

And while you're right those things can take lifetime, we're quite lucky to have our fellow brothers and sisters.. mice!
First immortal lifespan anyone?
Once an already middle aged mouse will get therapies and turn to be about.. 10-15 years old and still healthy, we'll know we're right.

[Traclo]

So winterbreeze you suggest that we know everything about the damage cause by metabolism? Of course it is defective (in a sense) in that we age, but my question was if we know all the damages. If you are sufficiently educated on these processes then please tell me that we are aware of every single damage caused. My apologies for questioning your credence, but I only assume the presence of human ignorance to some degree or another.

Concerning the issue of application of damage repair, we may know that we have it generally right through the mice (which I thank you for) but my concern is the human trials, which will inevitably take considerably longer. The FDA does not let it go at mice testing, and I'm unwilling to put all my chips on mouse aging being identical to human aging. I agree that it is a valuable place to test our attempts but I was more concerned with the human trial length and fact that the human trails may eventually fail. Which is why I would advocate a comprehension first approach, one which I plan on pursuing.

If someone could enlighten me on the specifics of the application differences of mice and men, or point me towards a paper covering the topic, it would be much appreciated. Also if someone could address the issue of us potentially being wrong in our engineering, and thus wasting very valuable time, vs first attempting to understand the system. As already stated I'm inclined to agree with maestro that it will be very hard to retrieve this information in a meaningful way, i.e. analysis, but my initial question was: Anyone who knows, are we confident in our knowledge of the results of aging?

[maestro949]

Considering that as maestro says there may be layers of damage (it's what I got out of it, perhaps not what was intended but it suffices to express my idea, apologies maestro if that isn't what you implied)

The complexity of damage I refer to is really the diseased state of an aged person where entire networks of systems are compromised. The cardiovascular system, the immune system, endocrine system, etc. The proposed fixes are simply not sufficient in my opinion. We need to go deeper into the network and cells as our understanding is lacking. It's 2007 and we don't even know why blood pressure goes up with age. Grrr. We only get 3 billion heartbeats and there's no suitable replacement heart or tissue repair mechanism in the works. Only the hope of stem cells. This is the case among all our systems. This worries me greatly. I want a sure bet!

Even Aubrey admits that some of the damage is very sophisticated and will be challenging to fix:

Several types of intracellular damage are highly challenging--sophisticated cellular and genetic therapies will be needed to combat them, which are surely at least 20 years away and maybe much more. Extracellular damage, by contrast, generally appears more amenable to pharmaceutical repair which may be feasible in a shorter timeframe.

Source

[:o]

[maestro949]

Oh, and that 20 years that Aubrey mentions? There's a day for day slip as nothing gets done. No progress 5 years from now? Still 20 years! OK, maybe 19 due to systems biology advancements. [tung]

[John Schloendorn]

I want a sure bet!

There is no sure bet. The closest thing to a sure bet is that everybody will die, including you and me. Once we accept this truth, we are grounded firmly enough in reality to think about ways to improve our chances. Decisions under uncertaincy may not be fun, but it's as good as it gets in this case.

Btw, Aubrey's infamous estimate is actually a 30 year one (10 for RMR, 20 after RMR), and contingent on $1bn SENS funding in the first 10 years and much, much more later. That's one reason there has been little apparent progress.

[Luna]

The closest thing to a sure bet is that everybody will die, including you and me.

I refuse to die [tung] that's why I do everything to improve the chances

But anyways, although aubrey predictions includes 1bn$ dollars funding and everything, we must remember, we do get (actually, even greater funding) money for researchs we want.
Although not directly related to sens, stem cells seems to be getting alot of hype now and funding.. great results too.
http://www.news.com....5006007,00.html

ofc, focused research will hasten the progress.

[John Schloendorn]

I refuse to die

Others tried that. They're dead.

Although not directly related to sens, stem cells seems to be getting alot of hype now and funding

Right. That's why they're not directly supported by the MF. People are kind enough in this case to do much of the required work by themselves, and they are doing great. But of course cell replacement is an excellent example of the damage-repair paradigm.

[niner]

Well I don't know as much about biotechology as you do but I would. It baffles me why you do not want a digital backup of your genetic code for future rejuvenation therapies.

If/when we get to the point that having my genome in digital form would do me any good, why would I want my current genome? I would like a better one.

[niner]

The complexity of damage I refer to is really the diseased state of an aged person where entire networks of systems are compromised. The cardiovascular system, the immune system, endocrine system, etc. The proposed fixes are simply not sufficient in my opinion. We need to go deeper into the network and cells as our understanding is lacking. It's 2007 and we don't even know why blood pressure goes up with age. Grrr. We only get 3 billion heartbeats and there's no suitable replacement heart or tissue repair mechanism in the works. Only the hope of stem cells. This is the case among all our systems. This worries me greatly. I want a sure bet!

I think that you are overestimating the difficulty of the problem. If, for example, we develop a reliable method to remove AGEs from proteins, that will fix untold problems that result from compromised protein structure. We don't need to understand those problems; they will be fixed automatically by changes made at a lower level. If or when SENS is implemented, we will have plenty of human guinea pigs running around that we can study and figure out what we missed. BTW, I think that we do have some idea why bp goes up with age.

[caston]

Well I don't know as much about biotechology as you do but I would. It baffles me why you do not want a digital backup of your genetic code for future rejuvenation therapies.

If/when we get to the point that having my genome in digital form would do me any good, why would I want my current genome? I would like a better one.

You wish you were somebody else?

[niner]

You wish you were somebody else?

No, I'd like to be me, but stronger, healthier, smarter, and better looking. I'd also like to be able to shoot laser beams out of my eyes.

[caston]

Apart from the shooting laser beams out of your eyes your genome does not prohibit you from having these things. Attractiveness is a reliable indication of general health and both intelligence and strength can be built up through practical mental and physical exercise.

I'm advocating that stem cells from bone marrow and hair follecules should be stored, sequenced and stored digitally so that in the future you can use that information to restore yourself to your current level of health. This could be a commercial service that also raises money for SENS.

[maestro949]

There is no sure bet.  The closest thing to a sure bet is that everybody will die, including you and me.  Once we accept this truth, we are grounded firmly enough in reality to think about ways to improve our chances.  Decisions under uncertainty may not be fun, but it's as good as it gets in this case.

That's just it. I've accepted this truth for our current state + optimistic projections that we'll make some very good headway with cancer and stem cells in the next two decades. But even with that optimism and even if SENS gets the $1BN I think we're all dead with current plans. Scientific progress currently moves far too slowly from theoretical --> practical implementation and $1BN is a drop in the bucket for what will really be needed to flush out all of the necessary fixes for reaching escape velocity. I'm guessing $50BN and 50 years with the current process. And that $50BN is nowhere in sight. The $1BN is nowhere in sight so I think we will need to be extraordinarily creative if, as elrond says, to beat our wings just right for any hope that we'll see anything remotely close to accelerating this process.

Only a complete paradigm shift that ripples through society and the scientific community is going to generate the synergy needed. What is needed? Some type of viral, open and distributed science project focused on biological processes in general where everyone can contribute. One that grips the masses such that everyone can pitch in whatever skills and time they have. If we can't bring the resources to the science, lets bring the science to the resources! Lets design a process that anyone can engage in and contribute to the science at the best level they can achieve.

If complexity is our biggest obstacle, then I propose we lay out a roadmap for a complete and comprehensive attack on it that includes anyone that can click a mouse and keys on a keyboard. The first step is actually one that everyone can participate in: Curating the data. We should be able to lay down a framework that allows everyone to just start puzzle building every piece of biological data into their appropriate slots. Those slots are machine readable data sets. As this puzzle unfolds, the scientific, academic, open source and biotech communities can start leveraging it in a variety of ways. Tools, games, statistical models, functional models and simulations can be built on top of this for gleaning more and more useful information as to how we can fight all diseases throughout the myriad of complexity.

I think that you are overestimating the difficulty of the problem.

Actually, I'm more concerned that I am still underestimating the problem. I am concerned that even with the full systems knowledge of the complexity AND an army of scientists fully engaged in trying to come up with clever ways to mop up damage in these networks, we will still fail. I was only half kidding earlier when I suggested that it might be easier to simply redesign ourselves from the ground up with the exception of the brain.

BTW, I think that we do have some idea why bp goes up with age.

Hunches are useless. We need precision if we're going to do any real engineering. Strategic Guestimates for Negligible Senescence isn't going to work. Besides, it's a crappy acronym.

[caston]

If we took all the money that wasn't allocated to curing ageing and we decided it was allocated to a single (in the context of biology) purpose what would that purpose be?

[Luna]

Extending life indefinitely :D

But if you mean one subject out of them.. Probably Stem Cells?

[caston]

Extending life indefinitely :D

But if you mean one subject out of them.. Probably Stem Cells?

I'm not exactly sure what the answer to my question is myself but if all that money is allocated to something other than curing ageing that thing ... whatever it is must be very powerful...

Maestro: I rememeber you saying that you weren't even sure if quantum computing was possible given what you understand about it so far... but if we do get a quantum computing revolution kicking off in the next decade how do you think it could benefit a systems approach to fixing metabolism?

[niner]

If complexity is our biggest obstacle, then I propose we lay out a roadmap for a complete and comprehensive attack on it that includes anyone that can click a mouse and keys on a keyboard. The first step is actually one that everyone can participate in: Curating the data. We should be able to lay down a framework that allows everyone to just start puzzle building every piece of biological data into their appropriate slots. Those slots are machine readable data sets. As this puzzle unfolds, the scientific, academic, open source and biotech communities can start leveraging it in a variety of ways. Tools, games, statistical models, functional models and simulations can be built on top of this for gleaning more and more useful information as to how we can fight all diseases throughout the myriad of complexity.

The data is far less complete and far more inaccurate, I fear, than you might imagine. How can a random person sitting in their bedroom or their mud hut curate data that they know little or nothing about? If you want to properly curate drug screening data, a good start would be a mass spectrometer, which the average computer user probably lacks, not to mention the sample, if it still exists and hasn't further degraded.

[maestro949]

Maestro: I rememeber you saying that you weren't even sure if quantum computing was possible given what you understand about it so far... but if we do get a quantum computing revolution kicking off in the next decade how do you think it could benefit a systems approach to fixing metabolism?

The pinnacle of systems biology from our perspective will be when we reach a point where an aging human being can be simulated and when it can answer questions like:

1. What changes to the system would minimize its rate of change (i.e. it's rate of aging).
2. For changes that have taken place (i.e. damage), what is the most economical and optimal option for reversing them.

Even with huge leaps in computing horsepower answering these questions are a long way off because we still have the task of flushing out the remaining omics and biomarker data and it will still be necessary to build the numerous models for and across the various scales described earlier in this thread. The horsepower will particularly help for the low level physics engines that future drug design and inference systems/libraries will sit atop.

We don't need to achieve that level of sophistication or horsepower for systems biology to contribute to reaching escape velocity though. Even with the small amount of omics data we do have, informatics is churning out some really impressive results across many fields of biology. I don't see a heck of a lot that spills over into aging research yet (mostly because we're lacking biomarker data) but the models are certainly increasing in complexity and usefulness due to some rather clever algorithm designs to get around some of the inherent challenges. Via datamining and statistical analysis along with biomarker data, we'll be able to identify numerous additional targets that directly or indirectly relate to the aging process and even several that are the cause of other miscellaneous damages. Of course we'll still need to validate these in the lab and through trials but I believe the time for major investments in systems biology is now. We can get going on designing the complex aging models now despite the lack of horsepower. It'll be here at some point and for where it's lacking, there's always inference.

One of the beauties of systems biology is that it will add value at every stage of growth in :

1. data (omics + biomarkers)
2. computational horsepower
3. sophistication of the models we build (those scales)

As each increases, so does the value these systems will yield.