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Google Summer of Code 2014 Ideas

From Open Bioinformatics Foundation
Revision as of 13:04, 14 February 2014 by EricTalevich (talk) (Cross-project ideas: Added JSBML idea #6)
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The details of each of our project ideas are listed below, including potential mentors. Interested mentors and students should subscribe to the OBF/GSoC mailing list and announce their interest.

See the main OBF Google Summer of Code page for more information about the GSoC program and additional ways to get in touch with us.


Cross-project ideas

BioInterchange: Convert and Exchange Biological File Formants using RESTful web service

Rationale
BioInterchange Interchange data using the Resource Description Framework (RDF) and let BioInterchange automagically create RDF triples from your TSV, XML, GFF3, GVF, Newick and other files common in Bioinformatics. BioInterchange helps you transform your data sets into linked data for sharing and data integration via command line, web-service, or API. BioInterchange was conceived and designed during NBDC/DBCLS's BioHackathon 2012. Architecture and RDF serialization implementations were provided by Joachim Baran, Geraint Duck provided JSON and XML deserialization implementations and contributed to architecture decisions, guidance on ontology use and applications were given by Kevin B. Cohen and Michel Dumontier, where Michel brought forward and extended the Semanticscience Integrated Ontology (SIO). Jin-Dong Kim helped to define ontology relationships for RDFizing DBCLS' PubAnnotation category annotations. The main idea is to have a central service with can be used as a validator and as interchange service for different languages.
Approach
The project will identify the most common and used file formants for all the currently used language under OBF and will design a RESTful API and will project an implementation for all the supported languages. BioInterchange was developed with Ruby but the scope of the project is to have an agnostic system which let use implement a converter using the best language for that functionality. It expected to have a high traffic for the service so an appropriate refactoring or reimplementation using parallel techniques or languages devoted to parallel programming would be possible.
Difficulty and needed skills
The project is mid / high difficulty, aimed at talented students. Previous knowledge of Ruby or other scripting language is preferred and flexibility in learning other languages is requireed.
The project requires
Knowledge of advanced programming languages and meta-programming and some concept in parallelizing and web services design.
Mentors
Raoul J.P. Bonnal, Francesco Strozzi, Toshiaki Katayama, Joachim Baran

Language APIs for the Systems Biology Markup Language (SBML) through the JVM

Rationale
The standard Java implementation of SBML, JSBML, is used as a parser for various Java-based systems biology applications.

This fulfills one niche, but the versatility of the JVM can be utilized to employ JSBML as a parser for systems biology applications that are written in other languages. Also, JSBML undergoes an active community effort to be up-to-date with current SBML standards.

Approach
This project will aim to present language APIs for languages that may want to employ the SBML structure without building a parser from scratch. Matlab, Mathematica, and Python APIs will be the focus for this project.
Languages and skill
Java, optional: Matlab, Python, (other language)
Mentors
Andreas Dräger, Alex Thomas

BioPerl

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NGS-friendly BioPerl code

Convert BioPerl-DB to use DBIx::Class

Major BioPerl Reorganization (Part II)

Perl Run Wrappers for External Programs in a Flash

Lightweight BioPerl modules

Modern BioPerl: BioPerl 2.0 and beyond

Bio::Assembly

Semantic Web Support

BioJava

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JVM support and improvements for the Systems Biology Markup Language

See Native and JVM-based support for the Systems Biology Markup Language (SMBL)


BioPython

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Indexing & Lazy-loading Sequence Parsers

BioRuby

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An ultra-fast scalable RESTful API to query large numbers of genomic variations

BioHaskell

Optimizing a novel, very sensitive alignment method