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19

Welcome to Biology.SE. Am I remembering this incorrectly? Yes, you're remembering well. I think you're talking about slime molds. You'll find more information on the wiki page Is this the video you saw? These images are pretty cool. Is this even possible? Yes (given that it exists). There is no way to correctly answer this question as it really ...


12

The answer is chance or, even better, contingency. About your calculations, it is true that the theoretical sequences are almost unlimited, but the basic scaffolds are not. Very different sequences can fold into the same basic scaffold and have a similar reactivity/function. So, even if not all the sequences have been explored on this planet, most of the ...


8

kmm's answer is great and complete; I just want to add some of my points on what kind of data should follow Gaussian distribution. Unless you know from observation that a process doesn't follow a Gaussian distribution (e.g., Poisson, binomial, etc.), then it probably does at least well enough for statistical purposes. I won't fault kmm for this ...


8

You raise two issues, both of which might be better suited for stats.SE, but I think the questions are suitably biological to warrant an answer here. Do most biological processes follow a Gaussian distribution? Unless you know from observation that a process doesn't follow a Gaussian distribution (e.g., Poisson, binomial, etc.), then it probably does at ...


7

Cancer cells can be and are used in cell culture. HeLa cells were the first human cell line to be grown in culture and they were derived from a cervical tumor. That being said, Cancer cell lines would not necessarily be used for stem cell work. They have sustained too many mutations to study the type of questions that stem cells are used to study, though as ...


6

Parallel DNA helix can exist and this has been observed experimentally. However these structures are stabilized by Hoogsteen type base pairing [1,2] and not the usual Watson-Crick type pairing because the parallel conformation does not allow the latter (See the figure below). This elongates the hydrogen bonds and also causes a loss of one hydrogen bond ...


6

Is the standard Lotka-Volterra (LV) model an exact fit for insulin-glucose (IG) dynamics? No. Can a similar model built on the same principles capture most of the essential features of the IG dynamics? Absolutely. How to capture most of the insulin-glucose dynamics using a slightly modified Lotka-Volterra model We can figure out how to change the LV ...


6

Adding onto AMR's answer, cancer cell lines are used extensively for research. They are typically fast to grow. HeLa Long grow to capacity of a 10cm dish within about 48hours, depending how you split them. Now some lines are different than others and each have their pros/cons but the main thing behind them is they make it possible to view the effects of ...


5

These kind of equations (the Michaelis-Menten [MM] like term) denote saturation kinetics. The basic mechanistic assumption behind saturation kinetics is this: A rate (of lets say product formation) is dependent on the concentration of a molecule such that the rate increases linearly with increase in the concentration of the molecule. Example 1: Substrate ...


5

The question appears interesting and made me think but I might not fully understand it. Let me know if I am answering your question. Genetic algorithm vs simulation of evolutionary processes I think that the whole issue comes from a confusion between the concept of simulating evolutionary processes and the use of genetic algorithm (type of optimization ...


4

First of all, there is a very heated debate about this in the field of social evolution at present, and you aren't likely to get a conclusive answer. One theorist may give you one answer, but another will vehemently disagree. I'll start by logically answering your questions in reverse order! Question 2: Can you please provide an intuitive explanation of why ...


4

Can we tell if a species will develop a specific character, based on the environment they're in? This is a major part of what quantitative genetics does. Or more detailedly, quantitative genetics can predict, for a population, changes in a trait given a selection pressure. First of all, for evolution to occur there must be variation in the trait you are ...


4

I'm afraid I laughed a bit when reading that paper for the first time. Why? Well, here's what they essentially did: They tried to model evolution by implementing an algorithm. They had a population of 10000 individuals, represented by their genetic sequence, and had an algorithm do mutations of those sequences and modeled selection and reproduction to get ...


3

A Poisson process follows these postulates: $\lim\limits_{h\to0+}\frac{P(N_h=1)}h=\lambda$ i.e. the probability of occurrence one event in a very small interval of time is equal to the macroscopic rate or intensity ($\lambda\,$). $P(N_h\geqslant2)=o(h)$ i.e. the probability of occurrence of more than one events in an infinitesimal interval is essentially ...


3

The writings by Samir Okasha (philosopher of biology/science) could be a good starting point. In his book Evolution and the Levels of Selection, he explicitly uses the Price equation to discuss selection at multiple levels (e.g. chapter 2.3: Price's equation in a hierarchical setting), and also derives a multi-level version of the Price equation: ...


3

John Harte's work on applying the mathematical theory of maximum entropy to ecology is certainly one of the better known examples of the application of this area of mathematics to science, in part because he literally wrote the textbook: Maximum Entropy and Ecology: A Theory of Abundance, Distribution, and Energetics (Oxford Series in Ecology and Evolution) ...


3

Since you are asking for the biological interpretations about these parameters, it is important to realize that the model you are presenting is a non-dimensionalized version of this model: $$ \frac{dx_1}{dt} =b_1x_1\Big(1- \Big(\frac{x_1 + \beta_{12}x_2}{K_1} \Big)\Big) $$ $$ \frac{dx_2}{dt} =b_2x_2\Big(1- \Big(\frac{x_2 + \beta_{21}x_1}{K_2} \Big)\Big), $$ ...


3

Regarding your question about whether cancer cells could be used in studying stem cells: I have done stem cell work, and we used various teratoma cell lines (which are cancers that resemble germline tissue) in parallel with embryonic stem cells (ES cells) and induced pluripotent stem cells (iPS cells) for various experiments. Of course the choice of ...


3

I figured it out, t' is just a dummy variable used to represent time over the refractory period since the integral is from t-r to t.


3

Theoretical ecology From wikipedia Theoretical ecology is the scientific discipline devoted to the study of ecological systems using theoretical methods such as simple conceptual models, mathematical models, computational simulations, and advanced data analysis. Effective models improve understanding of the natural world by revealing how the dynamics of ...


2

No it isn't necessary to breathe in CO2 from the atmosphere. For the buffer system your brain detects the amount of CO2 (H+ which is an indicator of excess or too little CO2) and adjusts your breathing automatically to compensate so that your blood's pH stays normal. No outside CO2 is needed. Your kidneys also play a similar role but the lungs are what ...


2

One example of what you may consider to be a macroevolutionary change is a whole-genome-duplication, or polyploidy event. These are not uncommon in plants, and can promote speciation due to a reproductive barrier arising between the polyploid progeny and the diploid parents. You can find many papers about this topic, here is one from 2009: ...


2

His notion of systemic mutations involved the postulation of massive chromosomal rearrangements (not mere recombination/crossing-over) as mediators of speciation in one-step. While whole genome duplications have been shown to induce speciation (see, for example, cryptic speciation in Hyla versicolor) they are not large scale rearrangements as he suggested. ...


2

Let's take the opposite extreme, $K=0$, so that each site has an independent effect on fitness. Without loss of generality, we can say that at each locus $n$, the $1$ allele confers an advantage $s_n$ over the $0$ allele. Then there is just one local optimum, the global optimum, at $\vec{1}$, so $M_1=1$ (and $P_m=2^{-N}$). The key difference is that in the ...


2

Interpreting your question as "would the Lotka-Volterra predator-prey model be a good model for the glucose-insulin system?" my answer is "no". The predator-prey equations capture assumptions about how prey and predator interact with each other, and how they would fare on their own. These assumptions are not equivalent to any reasonable assumptions about the ...


2

Reiterating the above comments. Have a look at Tajima's D. It provides an estimate for the number of segregation sites for a population under a neutral mutation model. The general form of the estimation for a diploid population is $E[S]=4N\mu\sum_{i=0}^{n-1} \frac{1}{i}$. Here the mutation rate of is per-genome not per-site, so $\mu=L * 10^{-9}$ where $L$ ...


2

The fraction of polymorphic sites that exist in a population is dependent on the biology of the organism. For instance, you would expect to find different rates of polymorphism in related plants that have different breeding systems, e.g. in Silene [1]. Past bottlenecks are also expected to decrease polymorphisms [2]. So, the answer to your question would ...


2

Your intuitions all seem correct. Coalescent simulation should be faster, because you don't track the entire population history over all t generations as you do in the forward simulation. Rather, as you work backwards in time you are tracking a smaller and small population. And with coalescent simulations it is probably very hard to incorporate the full ...


2

I've worked on a couple of these for biofuel production. The answer varies widely according to plant P and how well studied plant P is. In terms of what data is used, it includes but is not limited to: temperature, insolation, length of the day, cloud cover, rain, soil composition, soil type, soil density, other local effects like wind or pests, altitude, ...


2

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 ...



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