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(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 som
by xaa 14y ago
(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.
- jboggan 14y ago(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.
- xaa 14y agoOver-hyped? In my neck of the woods these approaches are treated with extreme skepticism for just the reasons you mention. For instance: De novo protein folding is not a solved problem, so how can a simulation predict dynamics for a protein whose conformation isn't even known? I'm sure in the year 2150 when my grandchildren go to the doctor to be scanned by the tricorder, the results will go to the full-cell (and full-body) simulator...but for now, I think bioinformatics is better served by sticking to higher levels of abstraction like transcript and protein counts (for disease modeling purposes).
- michaelgrosner 14y agoThe main message I got from talking to people involved in systems biology is that we don't even get qualitative agreement between simulation and experiment, nevermind any sort of quantitative data, on extremely well studied systems like the lac operon. It seems like we're at least 25 years away from decent models.
- sabraham 14y agoSorry to be late to the party-- xaa, could you explain a little more what you mean by "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." I don't know anything about bioinformatics, so I'm trying to see how this differs from vanilla automated model selection. I'm really interested, so please feel free to send me an email if you feel that's more appropriate.