CSSS 2008 Santa Fe-Tutorials

Open Source research software

Open (no pun intended...) your eyes to the wonderful world of FOSS -- Free and Open Source Software. While the distinction between Free and Open Source is a very interesting one (and highly contentious in the right crowds), for research purposes, we want to use the best tools for the job but some of us suffer from limited income, so I would like to talk about both. At the same time, FOSS is great to use for a non-economic reason: if you find bugs, or design extensions, you can fix them yourself (in OSS, at least) or at least report the problem back to a typically active community. Some potential tools to discuss/explore: R, Octave, Scilab, Gnuplot, perhaps some of the more useful languages in the field like Python and perhaps others I don't know as much about (a quick `apt-cache` on my Ubuntu Hardy install shows RasMol, ClustalW, SeaView, Achilles, complearn, EMBOSS, GENESIS, etc...)

R tutorial

I (Ruben) know a little bit about R (basic stuff such as common plots and regression analysis) but would like to enhance my R skills. Does anybody have an interest in a R tutorial, too? Please edit this if there is more interest.

Would be interested in learning about this as well. -Devin

Python tutorial

I've (also Ruben) interest in a Python tutorial. Please edit this if there is more interest.

I can give a tutorial on python and on scipy/numpy, its great scientific library Giovanni

Neutral models in biology

There is an interesting paper by Cosma Shalizi of SFI about methodological problems in social sciences research in which he talks about the concept of neutral models in evolution models. I was wondering if any of the bio-people can give a tutorial on this topic as I am pretty interested in understanding the concept. Giovanni

GIS

I (Flavia) could offer an introduction to GIS/Spatial Analysis. Please edit here if you are interested.

Statistical Physics for Non-Physicists

Problem: Textbooks about this are writen for physicists. Solution: A Physicist (or mathematician) that would be so kind and spend few minutes (or maybe hours) to explain all that stuff to people like me(Petr):-)

Ruben: Do you seek for a general introduction or something specific?

Modern Logic and Reasoning

Like I mentioned in the 'ice-breaking', I could tell something about application of modern logic into human reasoning. It's a very board topic, and very new. Criticisms are welcome and needed. I would give some basic examples. On top of that, I would also say some development of logic, and how I found it useful in research, which might seem un-related to logic, esp. in social science. I am planning to give a 15 to 20 minutes presentation, UNLESS people want to hear more, in that case, please let me know. QiQi

I'm interested! Kathleen
Sign me up. — Josh

Introduction to the Design and Analysis of Computer Experiments

How do you find "interesting" behavior when your computer model is too slow or the inputs are too many to try every possible combination? Using an Arctic sea ice simulator example, I will show you how modern statistical methods can help you explore your virtual world more efficiently. Check out this brief overview or a more technical paper about global optimization. Time permitting we could also touch on some of the statistical concepts involved, e.g. cross-validation, maximum likelihood estimation, or Bayesian statistics. Béla

Genomics / Central dogma overview

It seems like some of you might be interested in an overview of the central dogma of molecular biology to non-biologists. This could be an 1h tutorial on the major actors of gene expression: nucleus, chromosomes, chromatine, DNA, RNA (tRNA, mRNA), proteins, polymerases, ribosomes, transcription factors, and eventually a quick intro to small, non-coding RNAs as a bonus. Although being a bioinformatician by training, I'm happy to leave the way if a "hard core" biologist wants to do this tutorial (Molly ?). Edit if interested! Jean

Artificial Intelligence/Machine Learning

I (Nish) could introduce some of the basic methods in AI/ML. If there is significant interest in the two fields separately, I could do two tutorials. Would probably focus on the higher level, rather than the nitty-gritty details, as well as applications of the methods to real problems. I'm not necessarily an expert, although have a fair amount of experience in the area, so I would prefer a more interactive session, where questions can be answered by everyone.

and perhaps others I don't know as much about (a quick `apt-cache` on my Ubuntu Hardy install shows RasMol, ClustalW, SeaView, Achilles, complearn, EMBOSS, GENESIS, etc...)

A Crash Course to Classical and Evolutionary Game Theory

Game theory is the study of interactive decision making. Classical game theory aims to develop a general theory to describe how rational agents interact strategically. In many cases humans lack the kind of infinite computational power and time assumed by classical game theory. In the early 1970s the biologist John Maynard Smith introduced evolutionary methods to the field, dispensing with the assumption of hyper-rationality while changing many of the concepts central to the field along the way. The result was evolutionary game theory. This new framework has been used to model the behavior of fundamentally non-rational players (such as viruses) as well as humans.

In this tutorial, I'd try to introduce the basic concepts in both of these fields, namely, the definition of a game, payoffs, the Nash equilibirum and evolutionarily stable strategies, the replicator dynamics. I'll briefly mention the three basic classes of two-strategy games represented by the Prisoner's Dilemma, the Snowdrift Game (sometimes called the Hawk-Dove game or Chicken), and the Stag Hunt Game. Depending on particular interests of the group, we could prove the Bishop-Cannings theorem and give a classification of all symmetric two-strategy games; or look at updating methods and spatial chaos; reputation and image scoring; rock-paper-scissors in biological systems; or evolutionary branching and specialization.

If there's something else you'd like to know about EGT, shoot me (Josh) an email, and I'll see if I can dig up something I know on your topic. I'm not going to require any fancy mathematical background. If you've seen a 2×2 matrix before, great. Otherwise, it's not a big deal. We won't multiply them or calculate their eigenvalues. They're just serve is a means of bookkeeping.