Today we have a pair of sites focusing on games to solve genetic and genomic analysis problems with blended crowdsourcing gaming approaches.
Phylo is a project from McGill University with some pretty heavy duty science behind it.
In their words:
"The comparison of the genomes from various species is one of the most fundamental and powerful technique in molecular Biology. It helps us to decipher our DNA and identify new genes. Though it may appear to be just a game, Phylo is actually a framework for harnessing the computing power of mankind to solve the Multiple Sequence Alignment problem."
Phylo is delightfully open source, with a Github site that not only shares the code but also the data, analysis, and also solicits language translators to bring the project to an international audience. Depite being originally released in 2010 it is still a very active project with ongoing support and recent updates to the code.
Gene Games is from Andrew Su’s lab at Scripps Research Institute, with an active team. Most recent presentations, blogposts and visible contributions have come from Benjamin Good, so keep an eye out in the future for his contributions.
Gene Games is not just one game, but right now four, and who knows what will happen in the future. These seem to more educationally focused for the most part, but not entirely.
"You and your partner see the same disease; each of you must guess what genes your partner is typing."
I’m guessing this one is less of a citizen science or crowdsourcing game and more entertainment for the geeks on their team. I suspect not very many people would have the requisite genetic background to see a disease and be able to start typing the genes involved.
You are shown one gene name
You are also shown five diseases
Pick the disease that is linked to the gene to get points
Get as many points as you can in one minute"
Again, more on the educational side, but assuming a fair amount of knowledge. I could see this being useful in teaching college level students, possibly even as an end of term assessment exercise.
The CURE (Play Games, Defeat Cancer):
This seems to be the main game, using crowdsourcing to deduce science rules within the data. Each "Mission" seems to be devoted to specific questions and challenges. The current one (Round 3) is devoted to predicting breast cancer prognosis, a very worthy goal!
In their words:
"The Cure is a serious, biology-based card game. Assemble the best hands and you can win – just like poker. The challenge with The Cure is that we don’t know the rules yet! Until you play, we can’t tell you if you have the equivalent of a royal flush or a pair of 2s. By playing the game, you will be both teaching and learning the rules of nature."
This is also an open source project, with code hosted on Bit Bucket.
Last but not least, Mobianga!
Mobianga is a fascinating game developed by 17-year-old Nishant Mandapaty to test gene-disease annotation.
"In Mobianga! you are presented with a series of genes and asked to find diseases that they are associated with. You score points based on the quantity and quality of the associations you suggest."
Now, aside from the fascinating story behind the development of the project, part of what excites me about this game is that it is so accessible to medical librarians and people with almost any kind of healthcare background.
"If you know anything about genes and their relationship to disease or are capable of using resources like OMIM, PubMed, and Google find such information he needs you to play a few games! "
Hey! That’s me! I can do that. And pretty much most of the people I work with. This could be an awesome office party some day, or maybe a special episode of the #medlibs Twitter chat, or a party at the annual MLA meeting … Evidently, they already thought of getting conference attendees to compete since they were offering prizes to people playing the game at the recent American Society of Human Genetics annual meeting.
Read more here in this post from their blog.
Gene-disease annotation with Mobianga