# Tag Info

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Dickinson (2005) has a good review of insect flight, including behavior, biomechanics, electrophysiology, and neural control with links to more of the primary literature. What follows is a general summary thereof. The jagged trajectories you mention are called saccades in the insect flight literature. In Drosophila, saccades are ~90° turns accomplished in ...

11

A Biologist's guide to mathematical modeling in evolution and ecology (Otto) is a very good book that is presented for people that have a highschool (or sligthly higher) level in mathematics. It makes a good review about all subjects that are usually taught to first year students in Biology such as linear algebra for example. It is highly accessible and in ...

10

Unfortunately it is not necessary to invoke group selection to answer this question. This is one of the reasons that Dawkins likes this discussion so much - he does not believe in group selection and so the discussion in SG does not invoke group selection. ESSs are described in the book as the product of direct competition or interaction between genes. ...

9

The probabilities are correct. You must take the product (in log space this is equivalent to sum). The reason the probability looks small is just that you are perhaps thinking the score should be close to 1. However, this is not the case. To get a score of 1, you need the PWM to have 1/0/0/0 at all positions and get a perfect match. So what should you ...

9

@Remi.b's list is excellent, but it should also include Gillespie's Population Genetics: A Concise Guide.

8

Quick search - Some articles that may interest you: 1) Random walk model of insect movements Kareiva P. M., Shigesada N. (1983). Analyzing insect movement as a correlated random walk. Oecologia 56(2-3) 234-238 2) Artificial life model of flying insects and its comparison to real insects navigation strategies. Dale K., Collett T. C. (2001). Using ...

8

When I think about your question of natural examples of XOR, it pushes me to think about what type of natural environments (i.e., evolutionary pressures) would lead to the selection of an XOR equivalent. When we implemented a synthetic XOR by "double flipping" one transcription terminator as a type of gene expression "check valve" it was the case that I ...

7

According to Deckmyn et al (2004), the primary effect of coppice management is that the fraction of total biomass in roots is relatively higher after coppicing, and that a substantial fraction of carbon in roots (~20% of root mass) is reallocated aboveground to support shoot growth in the spring following coppicing. Because of this large re-allocation, ...

7

This is a common experiment for microbiology courses and you can find instructions on the internet , here is an example from University of Wisconsin: http://inst.bact.wisc.edu/inst/index.php?module=Book&func=displayarticle&art_id=114 But the general method is measure optical density at regular intervals and plot them on a semilog graph, which has ...

6

You can use power analysis to work out answers depending on the specifics of your data. The things you need to consider are: The power of the test. This is the probability that the test will fail to reject the null hypothesis even if in truth it is false (Type II error). If the population is not in equilibrium, what is the probability that the test will ...

6

In an infinite, well mixed population with single pairwise encounters, Grudger is indeed not an ESS. In fact, as you correctly note, in such a model the Grudger and Sucker strategies are indistiguishable, as the probability of anyone encountering the same individual twice is zero. To make it possible for the Grudger strategy to survive against invasion by ...

6

The particular language a bioligist uses depends on the trade-offs between speed and ease of programming. Many models are written in C or Fortran if speed is paramount. On the other hand people will write models in higher level languages if speed is less important. These would be Python, R, MatLab, etc... In my models, which are written mostly in Python, ...

5

The Karr et al. paper attempts to capture most of the details in their model by combining features from the genome, transcriptome, proteome, and metabolome. This work heavily builds off of the coarse-grained models that you ask of especially on the work from Bernhard Palsson from which Markus Covert did his training. The answer to your question rests ...

5

The field most closely associated with game theoretic models in biology is evolutionary game theory. If modeling is required, then the typical paradigm is agent-based modeling, and a good introductory book is: Yoav Shoham and Kevin Leyton-Brown [2009], "Multiagent systems: algorithmic, game-theoretic, and logical foundations", Cambridge ...

5

Very little is known about the structure of fitness landscapes. H.A. Orr (2005; also Whitlock et al., 1995; Kryazhimskiy et al., 2009) explains that most experimental results do not actually attempt to measure the fitness landscape, but instead report just the average fitness versus time and average number of acquired adaptations versus time. This can't be ...

5

The frequency fluctuations will be determined by a standard model of selection as found in any basic population genetics text. In this scenario they take a very basic form: during each long period $i$ the frequency of $A_1$ increases from $f_i$ to $f_i\cdot (1+s_1)^{n_1}$ and during each short period $j$ the frequency of $A_1$ decreases from $f_j$ to ...

5

There are a number of more recent papers dealing with phylogenetic methods in reconstructing language history as well, including work by Colin Renfrew and Quentin Atkinson. Here are two recent high-profile papers. Unfortunately, both are still behind paywalls, but even reading the list of papers they cite / that cite them would be a great way to answer your ...

5

Although work in those areas is definitely all related, there are some kind of general differences in how those labels tend to be used, and I'll take a stab at defining them: Mathematical ecology - this is typically the creation of theoretical models composed purely from math (i.e. not stochastic computer models). Examples include a lot of classics from ...

5

The chaotic behaviour you are referring to (at least the one described in your link in the comments) is a property of the discrete version of the logistic equation, where you get chaotic dynamics at growth rates above ~3.55 (see the logistic map). The behaviour of this equation has been described in a classic paper by Robert May (1976). As you increase ...

5

Well, I think I found the very simple mistake I made… Looking again in my equations, I realize that (for some reason) $cor = 2 \cdot \frac{\sigma_A^2}{\sigma}$ And looking at this website, I see that the slope of the parent-offspring regression is $\frac{h_N^2}{2} = slope$ Here was my mistake!

5

That really depends on your system. At least for yeast the difference influences the strength of the activation ("Analysis of Transcriptional Activation at a Distance in Saccharomyces cerevisiae"). For bacteria such long distance regulations have recently been identified. Before that it was thought that this does happen only in eukaryotes. See the paper: ...

5

(This isn't an answer, but hopefully it will help get it past the experimental design into just solving the equation.) Where did you get that α0 was not determined from their data? On p. 10 (256), they state, "The prevailing direction of effective pollen dispersal within neighbourhoods (a0) that gave the best ﬁt of the model was 91 degrees from north ...

5

This is actually not the Fitzhugh-Nagumo model of the a neuron, however it is highly related to it. I believe the the Equation you have there, is capable of oscilations for any positive values of $\epsilon$, $C$, $L$. I generated this graph with the parameter values all set to 1. Note how it is very similar to a sine wave. I believe you where trying to ...

4

Classification of equilibrium points is done on the basis of the eigenvalues. If the two eigenvalues have no real parts, it is a hyperbolic fixed point and represents undamped oscillation. If both have a negative real part, it is a stable fixed point. If any of the eigenvalues has an imaginary part then it represents damped oscillations (in that case the ...

4

The amount of transfected plasmid does not correlate at all with the protein expression level. After transfction, usually each cell is going to get and keep only one copy of the plasmid. Once the plasmid is in the cell, it will be replicated and the cell will contain X copies of it, depending on the plasmid copy number. In general, plasmids with low copy ...

4

This is derived from studying how heterozygosity changes over time. The standard equation for change in heterozygosity ($H$) with constant population size ($N$) is: $H_t = \left(1 - \frac{1}{2N}\right)^tH_0$ When $N$ varies between generations you use the product of this formula: \$H_t = \left(1 - \frac{1}{2N_0}\right)\left(1 - ...

4

Just need to solve the equation. p1 = X11 + X12; q1 = X11 + X21; 1 = X11 + X12 + X21 + X22. D = X11 - (X11 + X12) * (X11 + X21) D = X11 - (X11X11 + X11X21 + X11X12 + X12X21) D = X11 - X11X11 - X11X21 - X11X12 - X12X21 D = X11 * (1 - X11) - X11X21 - X11X12 - X12X21 D = X11 * (X11 + X12 + X21 + X22 - X11) - X11X21 - X11X12 - X12X21 D = X11 * (X12 + X21 + ...

4

There is one book that will perfectly suits your needs: A biologist's guide to Mathematical Modeling in Ecology and Evolution, by Sally Otto It is a very good book that is very easy to understand and in the meantime goes pretty far (It ends with the use of diffusion equation in Evolutionary Biology). I highly recommend it. It covers: How to create a ...

4

Indeed a very good question. I'm afraid it might remain without a proper anatomy-based answer, but my intuition would tend towards agreeing with "the smaller you get, the more deviation you'll find". Or rather, I would expect the same principle as in conservation of genetic patterns to apply here: the more central a tissue structure is to survival, i.e. the ...

4

This is a general answer for all three of your related questions: This one How does Temperature influences the rate of protein turnover? How is the rate of transcription influenced by temperature? Since you said: I want to simulate the evolution of genetic architecture when after a sudden change in temperature or in an environment that is ...

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