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by gone35
3064 days ago
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Interesting work! We definitely need far better inference models in computational biology than what we currently have. I agree with your paper that modeling is unfortunately more of an "art" than a science nowadays... and with huge societal consequences. Having said that, on a cursory read I think you may be misapplying Valiant's algorithm... In particular, the original (union bound) PAC guarantee relies crucially on IID samples, so you cannot straightforwardly apply it to time series data and expect the guarantee to hold unchanged. Instead, you should use block bootstrap methods to sample consecutive segments of your time series of a certain size --in which case a (possibly weaker) PAC-like guarantee might hold, provided the dependence across time decays sufficiently fast [1]. I'm also a bit concerned about the semantics of your approach, since I thought gene regulatory inference was/is notoriously intractable, and Valiant's model is very stringent and conservative... So IMO somewhere along the line you are getting a massive free lunch simply by reducing to k-CNF! Not saying it's wrong per se of course; but I couldn't easily tell exactly where the 'trick' is... So if I were you I would try to communicate more clearly (to dumb non-experts like me) how exactly this particular reduction captures something highly non-trivial in gene regulatory networks to achieve such a (seemingly) drastic speedup.. [1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4551412/ -- |
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Correct me if I'm wrong but I think the key step is the use of "positive Boolean semantics"; which, as your Ref. 9 proves, are substantially weaker --and hence, unsurprisingly, far more tractable-- than more conventional "stochastic" or "differential" semantics...
But then Ref. 9 [1] goes on to make, I think, a frankly astonishing, Church-Turing like existential claim in Biology (Sec 3.2, infra):
[...]if a behavior is not possible in the boolean semantics, it is surely not possible in the stochastic semantics whatever the influence forces are.
If that is the case, that would IMO have huge consequences! It would mean, then, that some of the underlying machinery of Biology may turn out to be far simpler than we think: no more pesky self-loops or bistable, mutually inhibitory modules to deal with! Tractable network inference, at last! It would potentially revolutionize computational biology, if true.
But, is it true? I think I see the intuition, but I don't think the case is as clear-cut, with that single "surely" carrying way too much of the rhetorical work... Indeed, the claim hinges on what I think is a rather interesting, non-trivial existential question: informally, if 'something' (of a given type) cannot be denoted in a certain weaker type, does that mean that 'something' cannot exist?
Anyway, not your paper per se; but I think it's an interesting debate nonetheless.
[1] https://hal.archives-ouvertes.fr/hal-01378470