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  • Chemical modeling - Using resources to model molecules and looking at the kind of molecule a certain combination of atoms make. Goes into using this kind of modeling to make new drugs. Would include a lecture that harks back to an (most likely) earlier lecture about how modeling is the third leg and then go into how drug companies have saved billions of dollars by being able to get through the early phases of drug development with just models. Would have a lab to come up with a feasible possibility for a new type of drug, and what it would/could possibly treat. Need to look into the availability of a computational chem server, as it might not be for use for beyond high school.
    • Molecular modelling (wikipedia) This has a whole host of potential softwares to use for this.
    • Ghemical homepage This is a software listed on the wiki linked above that I have heard of and have any kind of familiarity with. Though there are certainly many others and it would be a good idea to look at all or most of them in a fair amount of depth before making any decisions as to what software to use.
  • Possibly a more structured/simpler version of the parachute lab done in CS290. Obviously having them perform the parachute drops and such would not be feasible but we could have them start out with the videos and some figures and they would do the netlogo aspect of the lab for themselves.


  • Modeling a woodwind instrument - Could demonstrate how changing the hole positions would affect pitch/timbre. Might need some introduction to the physics of music, general properties of sound.
  • Modeling airflow in a wind tunnel - This could be introduced as a follow-up to the woodwind unit, except now the class could look at the increased complexity of airflow around a simulated object. How detailed and complex can a virtual object become before modeling airflow around it becomes computationally infeasible? This unit might be able to use some of the physics background introduced in the Woodwind modeling unit described earlier. The fluid dynamics aspect might add a significant learning curve, however.

Vlado [Hope mine makes sense]

  • Similar to Bryan's idea;Aerodynamics of an object:in try of reducing air drag with simulating different versions and simulations of a virtual object in air tunnel; improving it's aerodynamics - in purpose of enabling faster traveling but again trying to keep it safe. Air tunnel simulation basically - how would an object react depending on the material used and its shape/structure? How much does air affect its possible movement? And the direction of the 'blowing' and the movement of the object affects the simulation result. The idea started watching F1 'cars' - which try to use lighter materials so the weight doesn't affect speed, but also to improve very crucial factor - the aerodynamics of the vehicle. Must point out that this model would be based on the physics principles-so its that is the science side of it.

  • I also found the idea of observing the behavior, in the lunch rooms and similar objects, of different people very interesting. Basically simulating 'green' and 'red' dots, having social even together- more various 'colors' are possible depending on the circumstances. The purpose would be to try to predict/simulate and conclude on what basis people divide/group themselves in everyday actions and needs. Regardless of the place, the mentality of people shows in this situations; which has the psychological aspect to be thought in the course. More about human behavior could be learned, if all important factors are included to the simulation. It might be wrong, but I see it as firstly trying to include the statistical aspect of it; counting the different dots; and bring some statistic about it-trying to figure out and predict the chronology of the events. Very important to include all the info that we already know, (as I said) numbers, age, possible past behaviors, and similar.
    • P.S.Hope it is good effort - I still am confused, I admit-but I am getting there.


  • Protein Folding - From the PDB to an image of a simple folded protein. Uses existing models and simulation tools to take the description of a protein from the Protein Data Bank and generate a simulated protein from that. Running existing models, scientific data store, visualization. Requires a lecture on the underlying physics/chemistry/biology.


  • Assembling a phylogenetic tree - Look at models available from the bioinformatics toolbench and experiment with different ways comparing protein similarity. This could be tied into a lecture on protein folding as protein homology like indicative of phylogeny.


  • Lighting - Simulating a thunderstorm, including atmosphere, charged cloud, building on earth and etc. Estimating which area will get damages.
  • Fermentation food - Set up food and bacteria (e.g. milk and lactobacillus) and simulate how they get fermented and rotten.

Ian-- If we're trying to generate interest, I think it would be good to initially give them huge models of catastrophic events that, to put it crudely, feel "awesome":

  • Hurricane tracking-- like the data that was shown to CS128, we can have them simulate the paths of hurricanes, severity, etc.
  • Tsunami simluation-- similar to the above, except... with tsunamis.

--Just something to give them the ability to say "Well, WE just simulated a friggin' hurricane that tore across the east coast of the U.S." It might help plug them into the class.


  • Population dynamics, use a predator-prey model and talk about the underlying interaction between two (or more) species. Could do this with agent-based modeling and/or system dynamics modeling. We could talk quite a bit about ecology and species interactions and things that affect the stability.
  • Cladistics (constructing a phylogenetic tree). Start with a common protein or gene amongst a group of organisms and construct a model for how they diverged evolutionarily based on evidence from that gene. This could also start simpler with looking at homologies and analogies and constructing a tree based on that (old way), then moving to the more cutting research with the genes. Would give an opportunity to talk about the computing power behind searching large databases of proteins or nucleotides.