123

Biological examples similar to programming statements: IF : Transcriptional activator; when present a gene will be transcribed. In general there is no termination of events unless the signal is gone; the program ends only with the death of the cell. So the IF statement is always a part of a loop. WHILE : Transcriptional repressor; gene will be transcribed ...


19

There are certainly some comparisons that could be made between the way genes are expressed from DNA and logic functions, but they aren't great. But synthetic Biology is really a blossoming new field that is attempting to integrate logic functions into biology, see e.g. Siuti et al (2013). The above paper is a brilliant example of a group using bacteria to ...


18

DNA is not analogous to computer code which renders your search for similar constructs in it meaningless. To give a couple of simple examples why this is: Computer code has a sequential order of execution; DNA acts in parallel and out of sequence, it is not "executed". Computer code has a strict and consistent meaning so the line if x==4 : x=7 always does ...


14

Just to add to previous answers, but transcriptional interference (see e.g. Shearwin et al., 2005) can be seen as a form of IF-statement (or WHILE) in the sense that: if(x transcribed){not y transcribed} The interference does not have to be binary though, and more common are graded responses. Transcriptional interference can also take place at the RNA ...


10

As WYSIWYG said there is no equivalent for function calls, as there will always be some interference. However one could argue that some modular pathways (eg. apoptosis signalling) can be seen as a "code block" where a certain input will (almost) certainly lead to a certain effect. The analogy with function calls is that, in describing many different ...


7

For that you would need to understand the dynamical systems theory behind the loop. The point at which the oscillation starts is called the Hopf-bifurcation. I shall explain this in simple intuitive terms. Lets assume that Protein-X activates the production of Protein-Y which in-turn causes inhibition of Protein-X production. This is a negative feedback loop....


6

I don't work in ecology, but my first thought is that I would not expect any relationship whatsoever between diversity and biomass. Biomass simply means the combined mass of all life on the planet. If that mass consists of one extremely fat goat the size of the moon, or several trillion different organisms doesn't make a difference, mass is mass. Now, it ...


6

Quantitative in the context of biology is similar to chemistry, and means "how much of something there is" - for example, how much of a particular protein is produced under what conditions. Now, you might think this is a simple problem, just measure the protein/RNA/DNA and find out. However, it isn't quite as simple as that. Even if the best ...


5

The situation that you presented in which an entity A inhibits the production of another entity B which in turn inhibits A, is a positive feedback. In a network path or a loop the overall sign of the loop/path is the product of the signs of individual edges (interactions). In this case it is negative times negative which gives a positive sign to the loop. ...


4

SBML follows in the same vein as XML, in that it provides a standardized and flexible method for structuring information. XML and its ilk aren't just for making web pages, they're for sending structured datasets between systems and programs (in fact, XML is a fairly common configuration format). Why? Because the structure makes parsing simple (well, simple-...


4

The model used by Jamshidi et al. can be found in the BioModels database with acession no. MODEL1103210001 http://www.ebi.ac.uk/compneur-srv/biomodels-main/MODEL1103210001 A more recent model has also been described in Bordbar et al. iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological ...


4

This phenomenon of being insensitive to certain fluctuations is called robustness. The fluctuations can be of two kinds for an input-output device such as a gene that is activated by a signal: Fluctuations in the signal Fluctuations in the intrinsic parameters Signal fluctuations can be temporal but parameter fluctuations are not (parameters are supposed ...


4

I believe that what you are aiming to do is not possible with the mechanisms that you propose. In most transcriptional and translational genetic circuits, the limiting factor for switching state is dilution or decay rate. This is because genetic regulatory networks directly control rate of production, rather than concentration. Thus, even if your oscillator ...


3

Here there are a couple that I own: The "classic" from Uri Alon touches many of the topics you mention. It is easy to read and goes relatively deep into the methods. There seems to be a new edition (if you search it in Amazon it will pop up), but it was planned for last year's April and then delayed so no so clear when will be actually published. For the ...


3

My boss is a big fan of Repast HPC, but since Repast is a C++ framework it might not be the right choice for you. It takes a loooong time to write a good C++ program (even for someone who already knows the language fairly well), although it will run very quickly once it's written. A one or even two year long Master's program will end up going by surprisingly ...


3

You are right this is a typo. Equation 5 is just a restatement of the definition of the dot product of two vectors: $$\mathbf{u}_k^T\cdot \mathbf{x} = \sum_{i=1}^m u_{ki}^Tx_i$$ or written in another way $$\mathbf{u}_k^T\cdot \mathbf{x} = u_{k1}x_1+u_{k2}x_2+\cdots+u_{km}x_m.$$ In the text Equation 5 is stating that one can find a linear combination of the ...


2

Enzymes usualy have a relative narrow temperature optimum, for those of our body this is usually around 37°C. It is around 37,2°C in the morning and goes slightly up to 37,7°C in the evening (see reference 1 for details). The temparature optimum for most enzymes looks somewhat like displayed in the figure (from here, interesting to read): Enzymes are ...


2

As far as I know, there is no one model officially known as "the Human Metabolic Model", but the Recon 2 model, described as a "consensus" model and the most comprehensive to date in Thiele et al. 2013, A community-driven global reconstruction of human metabolism (http://www.nature.com/nbt/journal/v31/n5/full/nbt.2488.html) is available at http://...


2

Firstly, it is important to remember that Flux Balance Analysis computes theoretical performance limits, i.e, the theoretically optimal behaviour of the system with respect to the objective and constraints. When growing bacterial cells growing in culture evolve under selection pressure for biomass production, the theoretical limit on biomass production may ...


2

It is common that reactions in stoichiometric models cannot carry flux because there is a "dead end" metabolite somewhere. The problem may not be in the immediate reactants / products, but can be several steps away, and is not always easy to find. If you have a network visualization tool, one option is to highlight all reactions that cannot carry flux; ...


2

Regarding function calls: There are no equivalents of function calls. All events happen is the same space and there is always a likelihood of interference. One can argue that organelles can act as a compartment that may have a function like properties but they are highly complex and are not just some kind of input-output devices. and As WYSIWYG said ...


2

Metabolism ≈ Anabolism + catabolism Metabolism is the set of all chemical reactions happening inside a living body. These reactions can either breaks down big molecules and build up big molecules. The set of reactions the breaks down big molecules is called catabolism. The set of reactions that build up big molecules is called anabolism. Energy Generally ...


2

This was our causal loop. Fig-1 Our situation Oscillation is simply an up and down of something, occurring in repeat with time. Now let's see why it causing an oscillation. Fig 2. Analogy with toilet siphon. C = Cause. E = Effect. E(min)= minimum value of effect . E(max)= maximum value of effect (as much allowed by time delay). I've compared here this ...


2

Of course, that is possible. I'll give a simple example. If your protein (X) is an inhibitor of the other protein (Y), then when X falls, Y will rise. This would not really be "thresholded". There are many mechanisms that can lead to thresholding which include co-operativity (in the action of X) and positive feedbacks. How these mechanisms work would be a ...


2

If you apply quasi-steady state approximation for the complexes then you will get three equations for each of the complexes. Then you have to use the conservation law for enzyme to obtain the equation with respect to just substrate and inhibitor. If you try solving these algebraic equations, it gets very complex and difficult to solve by hand. However, in ...


2

Bistability referrers to two coexisting stable conditions (if you disrupt they will tend to restore to one of those two areas) and has a slightly broader application it can also involve chemical stability for instance. Bistability includes the element of stability (obvious in the name) if disrupted bistable condition tend to return to one of two stable ...


2

Progressive cell death along a spatial dimension would be consistent with this. For example, imagine a cylinder of tissue in which cells at one face die, inducing adjacent cells to die. This would yield linear decay in viability to 0.


2

I am assuming that in your model, the reactants and products (species) are metabolites and each reaction denotes conversion of one metabolite to another. From transcriptomics, you will get the relative expression levels of different genes. When you have two samples from different conditions you can calculate the differential expression. A model can be ...


2

I am not sure that I completely understand, it would be a little easier if you described the problem you are trying to solve or what the motivation is. However, I think that some of what you want to do can be accomplished by inferring gene/protein trees for each gene/protein of interest across different species (including paralogs, maybe?). This will allow ...


2

Let’s start by considering a very simple feedback loop, namely a system with just two genes A and B which repress each other. Such a system can be in two possible states (it is bistable): A is expressed and thus suppresses B, which is not or hardly expressed. B is expressed and thus suppresses A, which is not or hardly expressed. We may perfectly ...


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