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Team:Illinois-Tools/Resources
From 2009.igem.org
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* Graphviz | * Graphviz | ||
* Matlab | * Matlab | ||
| - | * | + | * COBRA toolbox (for Matlab) |
='''Journal Articles'''= | ='''Journal Articles'''= | ||
Revision as of 17:36, 21 October 2009
As a team who relied mostly on technology, we have a unique list of resources that we either used or investigated. The resources that we looked at can be divided into three categories: Software, Journal Articles, and Books
Software
This category includes all programs, libraries, modules, websites, and anything else involving computer technology.
Programming Language
For our web-based program, we used Python 2.5/2.6 programming language in conjunction with the web framework, Django 1.0.2, and MySQL, a relational database management system (RDBMS).
Modules/Libraries
- Biopython
- Networkx
- SciPy
- SoapPy (for KEGG API access)
- Pythongraph
- Pygraphviz (to work with graphviz)
- Pyexcelerator
- Pyopengl
- Matplotlib
Websites
- Kyoto Encyclopedia of Genes and Genomes (KEGG; www.kegg.jp; our main database that we obtained info from)
- Network Analysis Tools (NeAT; http://rsat.ulb.ac.be/rsat/index_neat.html)
Programs/Other
- Cytoscape
- Eclipse
- Graphviz
- Matlab
- COBRA toolbox (for Matlab)
Journal Articles
Becker, Scott; et al.Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox.Department of Bioengineering, University of California San Diego.Nature Protocols Vol.2 No.3. March 2007.
- Briefly describes constraint based modeling and give the principles behind it
- Describes the functions of the COBRA toolbox and it explains the output of the program
Price, Nathan; et al. Genome-Scale Models of Microbial Cells: Evaluating the Consequences of Constraints.Department of Bioengineering, University of California San Diego. Nature Reviews. Vol.2. November 2004.
- Describes the constraints one must take into account when creating genome scale models
- Explains each constraint in detail
Books
Lutz, Mark. Learning Python; 2nd ed. Sebastopol, CA: O'Reilly, 2004. Print.
Python cookbook; 2nd ed. Beijing: O'Reilly, 2005. Print.
