Open Bioinformatics Foundation

Web Page: http://www.open-bio.org/wiki/Google_Summer_of_Code

Mailing List: http://lists.open-bio.org/mailman/listinfo/gsoc

The Open Bioinformatics Foundation is a nonprofit volunteer run organization focused on supporting open source programming in bioinformatics. It acts as an umbrella organization for the BioPerl, BioPython, BioJava, BioRuby, BioSQL, and BioLib projects, and organizes conferences and workshops to promote and support open-source bioinformatics.

Projects

• BioJava - Amino acids physico-chemical properties calculation I’m applying for the amino acids physico-chemical properties' calculations proposed by Dr Peter Troshin. I intend to have 4 tangible products at the end of the project – A set of APIs, executable, SOAP and journal publications. On top of the proposed physico-chemical properties, I also intend to add structural, composition and additional physico-chemical properties such as those available via PROFEAT (PMID:16845018) and Sirius PSB (PMID:20014474) if Dr Troshin deems them appropriate.
• Interface analysis module for biopython In the aim to increase the information we can get from a pdb file, I would like to develop a module to produce significant and useful physico-chemical information on protein-protein interfaces. Complementary to parsing module already existing, it would be an easy-to-use way for a scientist to have basic information before launching more complex calculations.
• Major BioPerl Reorganization Contribute to the reorganization of the BioPerl project, by breaking it up into smaller distributions and publishing them to CPAN.
• Mocapy++Biopython: from data to probabilistic models of biomolecules Mocapy++ is a machine learning toolkit for training and using Bayesian networks. It has been used to develop probabilistic models of biomolecular structures. The goal of this project is to develop a Python interface to Mocapy++ and integrate it with Biopython. This will allow the training of a probabilistic model using data extracted from a database. The integration of Mocapy++ with Biopython will provide a strong support for the field of protein structure prediction, design and simulation.
• Mocapy++Biopython: Mocapy++ bindings for BioPython Biopython is a very popular library in Bioinformatics and Computational Biology. Mocapy++ is a machine learning toolkit for training and using Bayesian networks. However, Mocapy++ is implemented in C++ and does not provide any Python bindings. The goal of this proposal is to develop an easy-to-use Python interface to Mocapy++, and to integrate this interface with the Biopython project.
• Represent bio-objects and related information with images The goal of the project is to implement graphical functions into the BioRuby objects, which will allow biological data to be visualized and exported easily.