September 21, 2009 by Steve · Leave a Comment
Today is 25 years of David Braben and Ian Bell’s Elite video game. This isn’t really systems or synthetic biology, but back in 1984 it was the inspiration of Cambridge students David Braben and Ian Bell that captured the imagination of a generation who spent the next 25 years carving a name for themselves in the Elite universe. Published by AcornSoft in September 1984, Elite has long been considered one of the best video games of all time and inspired the whole “space trading” gaming genre with games such as Eve online, Freelancer, and the X series continuing the tradition. Elite was the first video game to create an “open universe” for players to explore and follow their own path as they chose, creating the concept of “sandbox” gaming popularized by the likes of Grand Theft Auto and Morrowind decades later. Long before the “RPG” scene emerged from dungeons and dragons with class based character development Elite enabled players to choose their own path as explorer, trader, pirate, bounty hunter, mercenary pilot, or all of the above literally doing as they pleased within a dynamic universe. Players could upgrade their ships to haul more cargo across the galaxy or more effectively vaporize the competition on their quest for “Elite” combat status. Explorers could roam over 2000 worlds across 8 galaxies, while budding entrepreneurs could chose to find lucrative trade lanes between planets trading between industrial and agricultural economies slowly making their fortune. Meanwhile more nefarious players could become bandits and pirates, stalking rich systems for cargo laden traders, living as a fugitive from deadly Viper police patrols, seeking refuge in anarchic systems dealing in contraband narcotics and slaves. Whatever your persuasion, Elite had a corner of the galaxy for you.
Many of the aspects of Elite sound routine in 2009, with the likes of Eve online, World of Warcraft, and Starwars Galaxies, but all this was available 25 years ago on an 8bit home computer with 32kb of memory and no internet and was an enormous computing achievement. Elite contained 8 galaxies, each with 256 planets which had to be procedurally generated. A single seed number was run through a fixed algorithm the appropriate number of times and created a sequence of numbers determining each planet’s complete composition (position in the galaxy, prices of commodities, and even name and local details — text strings are chosen numerically from a lookup table and assembled to produce unique descriptions for each planet). This means that no extra memory is needed to store the characteristics of each planet, yet each is unique and has fixed properties. Each galaxy is also procedurally generated from the first. Elite was a technical masterpiece of it’s time and remains unbeaten in it’s achievements and success.
For those who have never experienced the Elite way of life check out the 25th Anniversary website, or for those who fancy dusting off their old combat skills Oolite continues the legacy of Elite with community maintained content and development
… at least while a generation awaits Elite IV.
COPASI – Complex Pathway Simulator
September 9, 2009 by Steve · Leave a Comment
A few weeks ago I attended a modelling and simulation Copasi workshop run at the MIB by Professor Pedro Mendes. I had attempted to blog about it previously but lab work got in the way.
The workshop was a 3 day event detailing all aspects of the Copasi software, much of which can be found in chapter 2 of the “methods in molecular biology” (2009) Volume 500. 1-43, available as a preview here. (There is also a publication associated with Copasi by Hoops et al. (2006) Bioinformatics 22, 3067-74). I’m no mathematician, so my description of Copasi wont be the most accurate! For me, Copasi is a graphical user interface into the world of mathematical modelling providing an immediate step up in to the capabilities of Matlab and Mathematica armed scientists without requiring particularly large amounts of experience of programming or modelling. The software forms a fundamental toolkit of everything a biologist, or mathematician/computer scientist, needs to build models of systems of reactions and run simulations on them. You can enter your reactions using symbolic algebra equations such as those found in many standard biochemistry textbooks, or directly as systems of ODE’s so it is familiar to both wet and dry scientists. A large number of standard enzyme kinetics equations are available when creating your model such as Michaelies Menten types and hill equations as well as all kinds of inhibitor-substrate relationships, and the ability to enter your own.
At its most basic you can input reactions between species of compounds using symbolic algebra and then create plots of the behaviour or those species as they react together in your system over time. You can quickly gain a grasp however of the underlying power of Copasi when you begin to make more sophisticated enquiries of your system. Using the graphical interface you are able to perform a range of systems biology / modelling techniques from finding steady states, to metabolic control and sensitivity analysis. The real power behind Copasi comes from the advanced features however, particularly the parameter scan which is currently not available in any of the equivalent simulation tools and would require substantial programming experience in Matlab or Mathematica. The parameter scan enables you to set a certain parameter at a range of values and repeatedly run the simulation, plotting the output from each iteration. This, for me was a hugely powerful tool as you can test your model under a range of initial conditions, in a high throughput manner.
Copasi is also capable of performing parameter estimation, which allows you to input laboratory data into your model as parameter values and then fit your model parameter values to the data to “reduce the distance” between your model and your observations and reproduce in vivo representative behaviour. In addition, there are a number of optimization algorithms built into Copasi that can optimize your model towards an objective function, or find conditions under which the model behaves in some particular way. There are a wide range of algorithms pre-programmed into Copasi for these tasks including evolutionary programming, genetic algorithms, particle swarms, Praxis, Hooke and Jeeves and more. For the even braver modellers, Copasi can be used in conjunction with Gepasi, an older relative of Copasi that can be used to run multiple simulations simultaneously. For example, you can have multiple copies of a model representing a culture of interacting cells or systems and run multiple simulations on multiple interacting models!
Models can be imported and exported in xml and sbml format and ODE’s can be exported in LaTeX and MathML formats for transfer between different applications. Models from biomodels.net can be imported directly into Copasi and there is a feature to update model details from the Miriam database. There is also a command line version of Copasi that enables high throughput “automated” modelling processes to be run. The Copasi group is also working on a web interface enabling scientists to access the software through a web browser interface.
The comprehensive tool set available in Copasi provides a hugely powerful tool for the budding systems biologists to immerse themselves in the field of mathematical modelling and perform some fairly rigorous and comprehensive modelling techniques without prior experience of complex mathematical programming. It can also produce data for the biologist with a minimum of mathematical knowledge, providing some interesting incites for experimental hypothesis generation.
Copasi is available as open-source, and free for academic research from http://www.copasi.org, and is under continuous development by a core team of programmers as well as a community of users interacting through an active forum. The software is available for Windows, Mac, and Linux. If you’re currently wresting with Matlab or modelling in general, I would recommend Copasi as an excellent starting point to dive into the sometimes intractable world of mathematical modelling, particularly coming from a biological background.