The document describes two online games, Dizeez and GenESP, aimed at identifying novel gene-disease annotations through game play. Preliminary results from 713 games played by 180 players through Dizeez identified 4,585 unique gene-disease assertions, including 224 assertions not found in existing databases. Top associations identified four or more times and not in databases suggest novel gene-disease links can be discovered through game play. GenESP improves on Dizeez by adding social interaction, enabling different game types, and increasing scalability to collect more annotations without relying on a fixed set of correct answers. The games are available at http://genegames.org.

1. Online games for human gene annotation
Salvatore Loguercio, Benjamin M Good, Andrew I Su
The Scripps Research Institute, La Jolla, California, USA
ABSTRACT
ABSTRACT Dizeez: gene – disease annotation quiz Community building and educational aspects
Structured gene annotations are a foundation on which many Select the disease related to the clue Game review
bioinformatics and statistical analyses are built, however their gene. Guess as many as you can in
representation is quite sparse. As centralized biocuration one minute.
efforts struggle to keep up with the rate of biomedical data
generation, new models for gene annotation need to be Every guess adds weight to a link Connect players with
explored. between a gene and a disease. published information
Recently, online games have emerged as an effective way to on genes and diseases
recruit, engage and organize contributors to help address
difficult challenges [1] like online image tagging (ESP Game), Preliminary Results
protein folding (Foldit) [2], or multiple sequence alignment 713 games, 180players;
(Phylo) [3].
We present here two online games - Dizeez and GenESP - aimed Overall: 4,585 unique gene-
at identifying novel gene-disease annotations, i.e. gene- disease assertions.
disease links well established in the literature, but not yet Training Game
reflected as structured annotations. Preliminary results are 224 assertions provided more
provided from game play online and at scientific conferences. than once and not found in
These data suggest that even after limited game play, novel OMIM/PharmGKB.
gene-disease annotations can be mined from game playing logs.
Top associations
provided four or more
times and not found in
Play game prototypes at: http://genegames.org OMIM/PharmGKB.
Even after limited game playing, the Dizeez game resulted in the
identification of several novel gene-disease annotations.
Game Objectives
GeneESP: gene – concept association with a partner
Use the Knowledge Powers! Powered by MyGene.Info and
Phenotype • Capture general
MyGeneInfo box
community
knowledge in a WordClouds
gene pathway useful structure
gene
Community Gene Autocomplete
Guess what genes your partner
is thinking about when they
see ‘neuroblastoma’
REFERENCES
• Concentrate Improvements compared to Dizeez: 1. Good and Su (2011) Games with a Scientific Purpose. Genome Biology
2. Khatibet al (2011) Algorithm discovery by protein folding game players. PNAS
community knowledge • Reward new, useful annotations with points 3. Kawrykowet al (2012) Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment. PLoS One
and reasoning around • Add social interaction CONTACT
predicting a particular • Enable gene-gene, gene-disease, gene-function
Benjamin Good: bgood@scripps.eduSalvatore Loguercio: loguerci@scripps.eduAndrew Su: asu@scripps.edu
phenotype games on the same platform
• Increase scalability of annotation collection (does FUNDING
See Poster A40, ‘Combo’ Phenotype 1 We acknowledge support from the National Institute of General Medical Sciences (GM089820 and
not depend on a database of ‘right’ answers) GM083924) and the NIH through the FaceBase Consortium for a particular emphasis on
Phenotype 2 craniofacial genes (DE-20057).
.