Open-Phylo: a customizable crowd-computing platform for multiple sequence alignment

Citizen science games such as Galaxy Zoo, Foldit, and Phylo aim to harness the intelligence and processing power generated by crowds of online gamers to solve scientific problems. However, the selection of the data to be analyzed through these games is under the exclusive control of the game designers, and so are the results produced by gamers. Here, we introduce Open-Phylo, a freely accessible crowd-computing platform that enables any scientist to enter our system and use crowds of gamers to assist computer programs in solving one of the most fundamental problems in genomics: the multiple sequence alignment problem.

Open-Phylo is the first crowd-computing system that is open for the benefit of the whole scientific community. It uses the processing power generated by video gamers (Figure 1). At the first glance, Open-Phylo looks like a traditional web server. Users are asked to register to access our interface and upload their sequences. Input sequences are first aligned using one of the publicly available algorithms, forming the initial configuration for the crowd-based work that follows. Once the sequences are entered into our database, the submitter accesses the crowd manager: a private interface that implements the tools to manage and monitor the data. In particular, the workspace lets users identify, either automatically or manually, portions of the alignment on which the crowd-based improvements should be focused, that is, those for which puzzles, either short ‘casual’ 20-column subalignments or longer ‘expert’ 300-column subalignments, should be generated. The submitter can track in real time the number of times each puzzle has been played and the magnitude of the improvement to the alignment score achieved by the crowd. At any time, the user can remove from the pool puzzles that he/she feels have been played sufficiently often, or to add new ones. This functionality allows the submitter to manage the work of the crowd. Crowd-improved MSAs can be downloaded at any time.

DOI: 10.1186/gb-2013-14-10-r116

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http://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-10-r116