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22

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 ...


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

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

A Biologist's guide to mathematical modeling in evolution and ecology (Otto) is a very good book that is presented for people that have highschool level in mathematics (It makes a good review in linear algebra for example). It is highly accessible and in the meantime it goes pretty far as it ends up talking about the application of diffusion equation in ...


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

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 ...


7

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

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


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

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

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

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 ...


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

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

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!


4

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 ...


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 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 ...


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

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: ...


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 ...


3

There is a lot of variation in how and when deer shed their antlers. In most arctic and temperate-zone species, antler growth and shedding is annual, and is controlled by the length of daylight. In tropical species, antlers may be shed at any time of year, and in some species such as the sambar, antlers last several years. Some equatorial deer never shed ...


3

Have you heard of something known as "Occam's Razor" ? It says when you have multiple possible explanations/hypotheses then select the one which is simplest (i.e least number of assumptions) Same with mathematical models. Chemical kinetics models usually assume first order unless there is some evidence against it. Similarly, for enzyme kinetics, as long ...


3

He defines lineage selection as selection for traits which increase the fitness of a group of plasmids, rather than an individual plasmid with in a cell or a particular cell containing plasmids. He says that the unit of selection are "plasmid-host clades" : in other words the unit of selection is the group of closely related plasmids in separate cells. It is ...


3

A solid limit: k must be greater than zero. Unless you're talking about some cannibalistic species or something that isn't suited to the model at all. As long as the species is productive in the new environment: k is greater than 1. The population is probably growing or again you probably won't be using an exponential growth model. As mentioned before you ...


3

On the G6G Directory of OMICS and Intelligent software, I searched for "QSAR Analysis, and received two product abstracts: 1) SYBYL®-X Suite which contained: 3D QSAR: use the power of industry leading CoMFA in a new way to generate novel ideas for R-groups - predict the level of biological activity or potency based on structure-activity data, Not just ...


3

The following papers are a good starting point: René Thomas, Boolean formalization of genetic control circuits, Journal of Theoretical Biology, Volume 42, Issue 3, December 1973, Pages 563-585 <= A classic paper in the field. Thieffry D. Dynamical roles of biological regulatory circuits. Brief Bioinform. 2007 Jul;8(4):220-5. Remy E, Ruet P. From ...



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