Basically the question says it all, although I'm not sure if it has a single answer. Do you have any ideas what other biological problems can be gamified in the same way as FoldIt or Phylo games did, especially using already available bioinformatics tools?
I found attractive this proposal, browsing the IamScientist site:
..."We plan to develop a ''game of evolution'' for public enjoyment and education. This will be a user-friendly program, freely available on the web, that simulates bacterial populations in a multiscale model based the genome-based model of evolution that has been developed in Shakhnovich lab. A player will be challenged to find evolutinary routes by which bacteria survives in challenging environments and to observe how their genomes evolve in response to environmental and man-made challenges."...
The title of the project is: Bridging Scales in Biology From Atoms to Organisms and the source is the Shakhnovich lab at Harvard
I am a gamer myself and I think anyone who has played the Civilization series learned a lot about history and culture through playing that game.
Can that be applied to biological sciences? I am not sure. There seems to be two types of games. One that is designed to inform the public about biological concepts and one that aims to leverage the public's minds in solving certain biological problems.
Both types of games have mostly been scientific problems disguised as simple puzzle games. The gaming aspect has always taken a backseat to the biological question, which is perfectly understandable.
I think for a "biology game" to succeed and have the audience playing past that initial novelty factor period, it needs to actually have solid gameplay, not just solid science. And that requires a tremendous amount of experience to design. People who funds these projects probably don't care enough about the gameplay to budget the money to hire a game designer.
A recent article in GenomeWeb - Bioinform (requires registration) discussed three new games under development at Scripps. Paraphrasing from the article: Combo attempts to leverage the biological expertise of players in a "card game" to train classifiers for high-dimensional datasets, which can then be used to find consistent gene patterns in the data that could serve as predictors for particular phenotypes (e.g., breast cancer relapse). Dizeez and GenESP also attempt to leverage the biological expertise of players but are aimed at collecting gene-disease associations from published biological and biomedical literature. Dizeez is formatted as a single player quiz-style game whereas GenESP involves a pair of players who independently enter genes associated with diseases but get points for matches with their partner.