Open writing projects/Scientific Programming with Python and Subversion/Brainstorming/Story lines

From OpenWetWare

Jump to: navigation, search
This page is part of the Open Writing Project Scientific_Programming_with_Python_and_Subversion. (More Open Writing Projects.)


Contents

Possible Story Lines to Use within the book

We should shoot for 2 of these, but let's gather as many thoughts as we can think of.

Social Science that uses 'Maps'

Hard social sciences have the advantage that they can often be understood by many people, and we might have the hope of 'teaching' a bit of the science in our writing so that people unfamiliar with the topic can still read the book. Even better are ones that are inherently visual.


David :I like this general idea. There's a lot of interesting social problems many of them involving networks (influence adoption, information propagation, dynamics etc.) It's pretty accessible, but can also get quite hairy numerically.

Possible Examples

  • epidemiological discovery of cholera by John Snow in London (see his map of the wells infected with cholera) - we can easily teach the basic statistics involved and this could give specific context to doing statistics within python and advanced graphics

Bioinformatics

This has the advantage that the science can be explained to a wide audience and there is a LOT of freely available data for people to play around with.

Possible Examples

  • I once saw an example that used NCBI's Entrez to search for a gene that causes a disease in Mouse, then used a 'relatedness' search to find the gene in the Online Mendelian Inheritance in Man (OMIM) database to figure out what the gene could be in humans. It was nice in that it covered a lot of the public bioinformatics databases. We would have to beef it up in order to be able to teach numerics and such, but it is a nice context for searching the web for information with python, storing and parsing web related data files, etc. As is, not too strong on visualization.

Computational Chemistry

Depending on how involved we wanted to get, we could do a bioinformatic analysis of a disease target to look for homology, then some combination of cheminformatics, MM, QM, and visualisation. I think I have found existing python libraries for all of those tasks frowns, mmtk, PyQuante, and PyMol respectively.

Possible Examples

  • Here is a good example
  • For a more involved numerical example we could implement QM/MM, or some other advanced charge description in MMTK. Needn't be this, find some theory and implement it. That kind of thing.
Personal tools