Over the summer, an enterprising high school student named Nishant Mandapaty approached our research group about doing a project with us.  He found us through the “Crowdsourcing Biology” group that we created for the Google Summer of Code program.  To make a long story short, he has been doing good work for us ever since, quickly learning what he needs to on his own.

His primary contribution so far is a nascent game for collecting gene-disease connections called Mobianga!.  He is planning to submit the results of an experiment using this game to the Intel Science Talent Search, a prestigious national science fair.  But, he needs help if he is going to succeed!  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!  Even better, invite several of your friends to play a few games.

Help a 17 year old computational biologist reach his dreams, play Mobianga! today!

Mobianga contest at the American Society for Human Genetics annual Meeting

Next week, I will be attending ASHG at the Moscone Center in San Francisco.  I will be presenting a poster (number 3584W) on Wed., Nov. 7 from 3:15-4:15 about game applications in biology.  If you come by and can prove that you have played a game of Mobianga by identifying your name on the leader board I will give you a prize!  I will also be giving out a more substantial prize at the end of the meeting to the top-scoring player as of the morning of Saturday November 10.  Details on the ASHG Mobianga contest will be distributed at my poster.

Technical details

Mobianga! makes use of the human disease ontology to provide the opportunity to easily annotate genes at varying levels of granularity.  For each gene challenge, you start at the top of the hierarchy (e.g. choose between ‘disease of cellular proliferation’ and ‘disease of mental health’) and you work your way down to specific diseases.  At each step you earn points based on an algorithm that assesses the precision of the annotation and degree of consensus among prior players in a manner similar to the Herdit game for music tagging recently published in PNAS.  

The game is implemented as a Python-powered Web Application that runs in the Google App Engine.  The code is open source and he would welcome collaborators.  The game is intended to eventually run smoothly on phone-sized browsers (the name Mobianga came from ‘the mobile annotation game’), but this optimization has not yet been achieved.  Anyone that wants to help, please get in touch.