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Please bear with me as I'm intruding into your world from a computer science background.

In programming, once you have created a program, you know all functions of that program. Thus, 100% knowledge is achieved.

My question is, in the field of Biology, how much do we think we currently know about the human cell? Are all functions known (eg. 100%)? Are most functions known (60%)? Or do we know a miniscule proportion (1%~5%) of functions of a cell.

The reason I ask is I'm interested in the concept of simulating cells via computer. If we know about a given biological function of a cell, we could convert it into a mathematical function for use within a simulation. With simulations, you could simulate the cell's reactions to drugs, viruses, cell garbage cleanup, etc, based on it's defined functions. And the more functions we know about human cells, the better the simulation.

Thanks in advance.

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closed as primarily opinion-based by anongoodnurse, The Last Word, WYSIWYG, fileunderwater, Bez Oct 24 '14 at 10:02

Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center, please edit the question.

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    $\begingroup$ It's difficult to estimate this because, in cellular biology, one new discovery (be it protein-protein interaction, drug response, etc.) may reveal 20 different, novel unknowns. As a programmer who has undertaken a similar modeling project, you're going to need to focus on specific areas of interest (i.e. signalling pathways) for specific responses, and you'll have to trust that your simulation will not be perfect, nor even great. I hesitate to even put a percentage to it but I'd err on the side of "miniscule". $\endgroup$ – Luigi Oct 23 '14 at 23:23
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    $\begingroup$ There is a huge difference between designing a program and attempting to reverse engineer a program, as biologists are trying to do in biological terms with cells. We are only aware of some principles but many details are yet to be discovered and explored! $\endgroup$ – Bez Oct 24 '14 at 0:15
  • $\begingroup$ Can cellular functions be 'mapped' out in such a way where with some 'subsystem' and how it 'behaves' it's functions can be 'modelled' with useful precision not in terms of an accurate description but a description adequate enough to be useful in real medicine; like Harvey's model of blood circulation in the Heart and arteries and veins. At the time a breakthrough model but now not that accurate. At least a biological model can be made and refined. Can all cell functions be modeled like this without needing to discard any 'attempted' models? $\endgroup$ – user128932 Oct 24 '14 at 3:55
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    $\begingroup$ As @Bez stated there is a fundamental difference between understanding something self-contained that you've constructed and learning about something unknown. Also, knowing 100% of functions should roughly translate to prediction withour error, which is clearly not the case for biological processes. From an epistemological standpoint estimating the %-knowledge of natural systems is almost nonsensical, since it assumes that we can compare to a complete list of "truths", when all we know is what we have been able to observe so far. $\endgroup$ – fileunderwater Oct 24 '14 at 9:01
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As someone who has dabbled in both biology and programming, I assume you are referring to the theoritical ability of functional programming to simulate organic behaviour from well defined input. From that point of view, our comprehension of the human cell behaviour is currently near stone age level. The astounding diversity of homeostatic and signaling parameters in our body makes a realistic simulation of human cell normal behaviour largely out of reach, so don't even think about patholgic states.

The more data we will acquire, the more precise our simulations will be. Currently, our data acquisition methods are too primitive, and clearly are not deterministic enough to base computed simulations upon them.

Of course, this answer reflects my own opinion, but I dare think that most of my colleagues will adhere to that view.

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