Cytoscape: An Open Source Platform for Complex Network Analysis and Visualization
PLoS ONE : accelerating the publication of peer-reviewed science
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Calculus Online Book
Standard error of the mean
When you take a sample of observations from a population, the mean of the sample is an estimate of the parametric mean, or mean of all of the observations in the population. If your sample size is small, your estimate of the mean won't be as good as an estimate based on a larger sample size. Here are 10 random samples from a simulated data set with a true (parametric) mean of 5. The X's represent the individual observations, the red circles are the sample means, and the blue line is the parametric mean. As you can see, with a sample size of only 3, some of the sample means aren't very close to the parametric mean. You'd often like to give some indication of how close your sample mean is likely to be to the parametric mean. Here's a figure illustrating this. Usually you won't have multiple samples to use in making multiple estimates of the mean. This figure is the same as the one above, only this time I've added error bars indicating ±1 standard error. Similar statistics Example Web pages

THE LAB
Gephi, an open source graph visualization and manipulation software
Genetic Programming: Evolution of Mona Lisa « Roger Alsing Weblog
[EDIT] Added FAQ here: Gallery here: This weekend I decided to play around a bit with genetic programming and put evolution to the test, the test of fine art :-) I created a small program that keeps a string of DNA for polygon rendering. The procedure of the program is quite simple: 0) Setup a random DNA string (application start) 1) Copy the current DNA sequence and mutate it slightly 2) Use the new DNA to render polygons onto a canvas 3) Compare the canvas to the source image 4) If the new painting looks more like the source image than the previous painting did, then overwrite the current DNA with the new DNA 5) repeat from 1 Now to the interesting part :-) Could you paint a replica of the Mona Lisa using only 50 semi transparent polygons? That is the challenge I decided to put my application up to. So what do you think? Like this: Like Loading...

9 Mental Math Tricks
Math can be terrifying for many people. This list will hopefully improve your general knowledge of mathematical tricks and your speed when you need to do math in your head. 1. So, 9×9 is just 9x(10-1) which is 9×10-9 which is 90-9 or 81. Let’s try a harder example: 46×9 = 46×10-46 = 460-46 = 414. One more example: 68×9 = 680-68 = 612. To multiply by 99, you multiply by 100-1. So, 46×99 = 46x(100-1) = 4600-46 = 4554. Multiplying by 999 is similar to multiplying by 9 and by 99. 38×999 = 38x(1000-1) = 38000-38 = 37962. 2. To multiply a number by 11 you add pairs of numbers next to each other, except for the numbers on the edges. Let me illustrate: To multiply 436 by 11 go from right to left. First write down the 6 then add 6 to its neighbor on the left, 3, to get 9. Write down 9 to the left of 6. Then add 4 to 3 to get 7. Then, write down the leftmost digit, 4. So, 436×11 = is 4796. Let’s do another example: 3254×11. The answer comes from these sums and edge numbers: (3)(3+2)(2+5)(5+4)(4) = 35794. 3. 4.

Particles found to break speed of light
Trend map for 2010 and out to 2050
For the last few years Richard Watson of NowandNext has created annual trend maps based on city subway maps. This year he has been more ambitious, creating a highly detailed map with five time zones, ranging from 2010-2015 out to 2035-2050. For the previous three trend maps (shown at the bottom) I collaborated with Richard and we co-branded them with Future Exploration Network, however time pressures this year meant that I haven’t directly contributed to the 2010 map. It is still as rich and glorious as ever – spend some time delving into the trends ahead! – Ageing – Power shift Eastwards – Globalisation – Localisation – Digitalisation – Personalisation – Volatility – Individualism – Environmental change – Sustainability – Debt – Urbanisation Click on the images below for the original blog posts and full-size pdfs. 2009 Trend Map 2008 Trend Map 2007 Trend Map

Pearltrees
Creating photons from a vacuum
In the Chalmers scientists’ experiments, virtual photons bounce off a “mirror” that vibrates at a speed that is almost as high as the speed of light. The round mirror in the picture is a symbol, and under that is the quantum electronic component (referred to as a SQUID), which acts as a mirror. This makes real photons appear (in pairs) in vacuum. (credit: Philip Krantz, Chalmers) Scientists at Chalmers University of Technology in Sweden have succeeded in creating photons from a vacuum. The experiment is based on one of the most counterintuitive but most important principles in quantum mechanics: that a vacuum is by not empty, but full of “virtual particles” that are continuously fluctuating in and out of existence. The static Casimir effect, proposed by Dutch physicist Hendrik Casimir in 1948, involves two perfectly reflecting parallel mirrors that, when placed in a vacuum, will be attracted to one another. Ref.: C.

Pauls Online Math Notes