Episode #125 of the Stack Overflow podcast is here. We talk Tilde Club and mechanical keyboards. Listen now
21

The paper by Lobo and Levin is an attempt to learn a model that represents the inner workings of a biological system by fitting parameters to data. This is a common topic in "systems biology", a model-based approach to studying biology that is popular in some fields. Even for small systems, this is a phenomenally hard problem. Unlike most machine learning ...


20

The fruit, sadly, does not hang so low. Short version Lobo et al (the work you refer to) is a nice and not especially novel application of basic Systems Biology modeling approaches to the wound healing system in flat worms. The main barrier to the wider application of such work is the lack of the necessary experimental data. Lobo et al themselves don't ...


13

Overview Modelling has come on leaps and bounds over the last decade or so and in many cases has acted as a sometimes viable, and inexpensive substitute for experimental structures. How do you know when you get it right? Ultimately, one still needs experimental evidence to know when a model generated in silico is right. But there are ways of scoring a ...


9

Mechanistic model answers the how question. These models are usually biophysically detailed, and designed to be causal. Say you discovered a linear relation between blood pressure drug and heart rate. This would be a statistical model. It doesn't tell you how the two are related biophysically. One could build a detailed model that describes intermediate ...


8

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 ...


8

I don't believe you'll ever find the first work in bioinformatics (or computational biology, as you put it), however the field really began in the times of accumulating data about protein biochemistry. Computational biologists (before they had access to the computer) would be writing and analyzing morphologies and types of proteins with pencil and paper. ...


7

The two most common families of scoring matrices are BLOSUM and PAM. Each of them has a score for every possible alignment combination between the 20 standard amino acids1. They both do more or less the same job but have been derived using different approaches. BLOSUM matrices (image taken from Wikipedia) The BLOSUM matrices are built from actual ...


7

Another nomination, if you include infectious disease epidemiology as part of biology and hence computational simulations of epidemics as part of computational biology: Measles periodicity and Community Size, M. S. Bartlett, J. Roy. Stat Soc. A, 120(1), 1957. The computations were run on the Manchester computer. Possibly the most entertaining part of the ...


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 ...


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

Though I have not found direct access to a model (which is what I'm really looking for), I have found evidence of such modeling efforts. The CDC apparently put out a risk-assessment report in mid July discussing the results of such epidemiological modeling (reported by FivethirtyEight, ABC and others). The report (available here), suggests that the risk of ...


4

This is a tough topic, have a look at the following references and see, if they can help you: Structural modelling and dynamics of proteins for insights into drug interactions. Ligand entry pathways in the ligand binding domain of PPARγ receptor Pathway and mechanism of drug binding to G-protein-coupled receptors Molecular Dynamic Simulation and Inhibitor ...


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

If you abstract enough, anything cam be considered as a computational device. The issue with doing this with cells is the sheer number of variables. For any given cell, the following internal variables exist: Internal ion concentrations for dozens of ions of importance importance Internal concentrations of hundreds or thousands of various simple organic ...


4

There have been several Turing machines constructed using DNA computing. One of these machines has been used to solve the boolean satisfiability problem, another was used to solve the bounded post correspondence problem, both NP-hard combinatorial problems which are difficult for conventional computers to solve. Also, a DNA computer was constructed that ...


4

A scoring matrix is used to compute a score for finding identical 3-letter words or similar 3-letter words that takes into account the liklihood of one being related to another. Although these matrices are empirical, they encompass factors like the number of mutations required (which is why there are different matrices for different extents of divergence) ...


3

Christian, great idea to ask this question here before taking important decisions. Are those media articles a hype? Yes. Over the last 10 years I constantly see those hype stories in media about "revolutionary" large-scale-study/big data projects with mind-blowing numbers (gigabases, teraflops, terabytes, thousands of papers and hundreds of genes). ...


3

The equation in the OP has been updated to $(y-a)^2(y-a\theta)$ which yields the correct expansion. Therefore, by equating the coefficients, we obtain \begin{align} \alpha &= (2+\theta)a\tag{1}\\ \rho/\beta^2 &= a^2(1+2\theta)\tag{2}\\ \alpha/\beta^2 &= a^3\theta\tag{3} \end{align} Using equations (1) to (3), we get the desired $\rho$ and $\alpha\...


3

Absolutely, the two I've had the most success are working with a radiolabeled and a fluorescently labeled version of the drug. Many drugs autofluoresce as well and this can be easily tracked. When it's labeled as mentioned above microscopy or a luminometer, spectrophomoter or a scintillation counter can evaluate fractions or whole cells, or purified ...


3

A Markov model is a description of a system that follows a Markov process. In a Markov process the next state of the system is a function of its current state and does not depend on where from and how it started. For example Brownian motion can be called a Markov process. The transition from current state to next state is described by probabilities. So to ...


3

Here are a few metrics you can calculate to get you started. You can use R to perform these calculations. Net Diversification Rate (r) Net diversification rate is (rate of speciation - rate of extinction). You can calculate it using the bd.ms or bd.km functions in the geiger package for R. r = 1: r = 2: Tree Imbalance: Colless index (I) Colless's ...


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

I currently work alongside many biologists that are working on simulations of anti-microbial peptides in the membrane. These seem to have a similar mechanism to what you're aiming for — permeating the lipid bilayer. Presumably you have already come to the conclusion that molecular dynamic simulations are probably a good shot for exploring what may ...


3

Biology is a large field of knowledge! As you give examples drawn from population biology (logistic population growth and Lotka-Voltera models), I will assume you are mainly interested in ecology and evolution. For analytical models used in ecology and evolution, I highly recommend the book A Biologist's Guide to Mathematical Modeling in Ecology and ...


3

I suspect that what you are asking for is years in the future yet. Bear in mind that the use of CRISPR-CAS9 is just entering clinical trials for a very few, well studied diseases. Almost all the work with CRISPR-CAS9 is still limited to model organisms and tissue cultures. Are you referring to Adiposis Dolorosa? Apparently the cause is not actually known ...


3

MD is used for studying structural changes. Simulation of biochemical pathways involves the kinetics (you are not really looking at how enzyme structure changes when it binds to substrate). You can certainly pool all the modelling strategies together to make a hybrid multiscale model. There are many people who work on such kind of modelling approaches. You ...


2

This is a typical architecture of computation proposed as a model for ventral stream of visual processing in primates. It has a long history (e.g., Neocognitoron by Fukushima was 1980) and still widely accepted in machine learning (e.g., deep learning) and neuroscience. It is motivated by the organization of V1 simple cells and complex cells. Simple cells ...


2

Evolution Evolution is the accumulation of genetic mutations that results in phenotypic variation (physical characteristics) where surviving variations are more suited to the environment the organism lives in, thus allowing it to survive better and -- critically -- reproduce as-good-as or better-than its competing organisms. In terms of computer science ...


2

The question is very broad and it is impossible to correctly answer to it. I think you may not realize how much computation is everywhere. Here is a bunch of things for which I personally use modern computation power Population genetics simulations Simulations of developments (Gillespie algorithm and variants) Statistical analyses, incl. some analyses that ...


2

IMO irrespective of country and level (undergrad/Masters), if you can run a job on a High Performance Computing cluster or a supercomputer, you should mention that on your resume. And sure, you can use that in your statement, especially given the fact that not many have access to it, you had the rare opportunity and made full use of it. In my experience, I ...


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