liks between science and games. Going from how we learn from games to scientific discovery games through the use of games to teach science.

1. Scientific games
@AntTaly #GLASS2015

2. What are the links between
science and games
● Learning from games
● Teaching with games
● Scientific discovery games

3. Games and learning
● Found in nature as a way to learn
(i.e. selected by evolution)
● Used for learning historicaly
(e.g. war games in China)

4. How does it work?
● Feedback loop
● Effect of uncertainty
http://link.springer.com/article/10.1007/s11251-008-9073-6#page-1
http://www.sciencedirect.com/science/article/pii/S0360131513000481
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0103640#pone-0103640-g004

5. Effects of games on the brain
● Increasing Speed of Processing With Action Video Games
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871325/
● Gaming improves multitasking skills
http://www.nature.com/news/gaming-improves-multitasking-skills-1.13674
● Action Video Games Sharpen Vision
http://www.rochester.edu/news/show.php?id=2764
● “Real-Time Strategy Game Training: Emergence of a Cognitive Flexibility Trait”
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0070350

6. Can we learn useful things in a game
"I put my qualifications on my resume when I apply for jobs," Gillett said. "Here's my guild. Here's my
ranking. Here's my biggest online achievement. Some people look at it and say, 'What the hell is this?'
And others will be like, 'That's exactly what I'm looking for.'"
http://money.cnn.com/2014/06/19/technology/world-of-warcraft-resume/
Learning tecnical skills:
“TEENAGE GAMERS ARE BETTER AT VIRTUAL SURGERY THAN MDS”
http://www.popsci.com/gadgets/article/2012-11/teenage-gamers-are-better-virtual-surgery-medical-
professionals

7. GAMES AND TEACHING
● Many exemples of the use of non scientific
games in teaching
● Use of games to teach science, including at
the university level [our focus]

8. A classical exemple: MinecraftEdu
Math,
Biology,
Geography,
etc...
MinecraftEdu

9. Teaching with games
“The use of educational games within learning
environments raises motivation, increases
interest in the subject matter, intensifies
information retention, encourages
collaboration, and improves problem-solving
skills.” Schneider, Maria Victoria, and Rafael C. Jimenez. "Teaching the
fundamentals of biological data integration using classroom
games." PLoS computational biology 8.12 (2012)
Quoting: Michael D, Chen S (2006) Serious games: games that

10. Games can be used to
teach
Stegman, Melanie. "Immune Attack players perform better on a
test of cellular immunology and self confidence than their
classmates who play a control video game." Faraday Discuss 169
Immune Attack
http://ImmuneDefenseGame.com
• High school students
• First person shooter
game
• Significantly improves
understanding of
concepts in immunology

11. Educational games
Game Purpose
The DAS game Teaching data integration in bioinformatics
(in person, not online)
The Bioinformatics
Game
Introducing protein sequence and structure (mobile)
4bases Introduce DNA sequencing (mobile)
MAX5 Introduction to sequence comparisons with BLAST, concepts in distributed
computing. High school.

12. TBG – select a protein

13. TBG: fly around to hit the
next amino acid on your list

14. 4bases (Rostlab, masters
thesis)
Click the next base
in time as the
sequence scrolls by.
Introduces concept
of DNA sequencing
Click next
base

15. MAX5
• Goal: introduce the concepts and purposes of DNA
sequence comparisons (BLAST) and distributed
computing to high school students
• First person game set in 3-d world beset by an influenza
pandemic.
• http://gamestem.com/portfolio/max5-storyline-1/
Perry, Daniel, et al. "Human centered game design for bioinformatics and
cyberinfrastructure learning." Proceedings of the Conference on Extreme
Science and Engineering Discovery Environment: Gateway to Discovery. ACM,
2013.

16. MAX5 starting screen 1

17. MAX5 starting screen 2

18. MAX5 “blasting” to detect what a
sample is infected with

19. MAX5 BLAST analysis

20. MAX5 alignment viewer

21. MAX5 sample hunting

22. MAX5 parallel computing

23. MAX5, TBG, 4Bases,…
Plusses
• Useful introductions.
• Useful for recruiting.
Minuses
• Very high-level –
shallow learning.

24. Bioinformatics education games
Game Purpose
Foldit Protein folding
Phylo, Fraxinus Multiple Sequence Alignment
EteRNA RNA structure design
EyeWire Neuron image tracing
MalariaSpot, MOLT Blood cell phenotyping
Dizeez Gene-disease annotation
Genes in Space Copy Number Variation detection
The Cure Biomarker selection for breast cancer survival prediction
• All examples of gamifying tasks in
bioinformatics.
• None built for the purpose of education!

25. Genes in Space
• Fly a spaceship
• (oh by the way you are
helping cancer
research)
• 300,000 downloads 3
months..
• Cancer UK project.

26. The Cure game
Alternate turns
picking a gene
from a “board”
of 25
Your
hand
Opponent
s hand

27. Classroom uses
• The Cure story (Antoine Taly) http:
//tinyurl.com/talycure
• Goal: understand the concept of
Biomarkers
1. Watch short video
2. Play The Cure game (involves picking
genes useful for predicting breast
cancer survival)
3. Create custom predictive decision

28. Use of games/gamification in
bioinformatics education
Expressivity: Number and depth of learnable concepts
Fun
Benefits:
recruiting,
Rosalind.info
CACAO
Gamified: badges,
leaderboards, levelsLecture
course:
Typically no
game
elements
Classroom
The
Cure Foldit
Phylo
Max5
Game: you “play it”,
learning more
implicit, purposes
aside from education
Genes in
Space
EteRNA
Holy Grail
?
Cost $$
Cost $$

29. Finding educational
bioinformatics games
• http://www.sciencegamecenter.org/
• Lists about 95 games related to science
• 57 are tagged with “biology”
• 2 with “computer science”
• None focus on bioinformatics learning
objectives.
Melanie Stegman
Federation of American

30. Games with science inside
● Termitia
http://science-animation.tumblr.com/post/65611682883/retour-sur-les-premiers-mois-de-termitia-un-jeu

31. GAMES WITH A PURPOSE
The Cure
MOLT

32. FOLDIT
A Key exemple:
● pioneering work
● scientific results published in peer reviewed journals
● deep analysis of players inputs

33. Started with grid computing
● ROSETTA@HOME

34. Foldit

35. Seth Cooper, Firas Khatib, Adrien Treuille, Janos Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, Zoran Popović, Foldit players (2010).
Predicting protein structures with a multiplayer online game. Nature 446 p. 756-760, 05 August 2010.
Faire mieux qu'un ordinateur

36. What makes the players good?
→ strategy
Seth Cooper, Firas Khatib, Adrien Treuille, Janos Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, Zoran Popović, Foldit players (2010).
Predicting protein structures with a multiplayer online game. Nature 446 p. 756-760, 05 August 2010.

37. What makes the players good?
→ strategy
Seth Cooper, Firas Khatib, Adrien Treuille, Janos Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, Zoran Popović, Foldit players (2010).
Predicting protein structures with a multiplayer online game. Nature 446 p. 756-760, 05 August 2010.

38. Foldit players come from many
backgrounds
Top 50 players
Busn/finance/legal
largest group..
Majority have no training in
biochemistry
Cooper, Seth, et al. "Predicting protein structures with a
multiplayer online game." Nature 466.7307 (2010): 756-760.

39. THE CURE

41. PLAY = GENE SELECTION
Alternate turns
picking a gene from
a “board” of 25
Your
hand
Opponents
hand

42. SCORING
Cure Server
Score reflects accuracy of
decision tree created with
just the selected genes on
real training data

43. PLAY WITH KNOWLEDGE: GENE ONTOLOGY

44. PLAY WITH KNOWLEDGE: GENE RIFS

45. YOU WIN!

46. GENE SET OVERLAPS, SOME BUT NOT MUCH
http://bioinformatics.psb.ugent.be/webtools/Venn/
“Expert Gene Set”

47. CLASSIFIER PERFORMANCE WITH DIFFERENT
GENE GROUPS, DIFFERENT DATASETS
X-axis Test Set performance
Griffith 2013 data
Y-axis Test Set performance
Metabric training Oslo Test
Only difference between points,
are the genes used to build SVM
classifier
10 year survival
Yes
No
“Expert Gene Set”

48. PLAYERS http://io9.com/
these-cool-games-let-you-do-real-life-science-486173006
1,077 Players registered (one year)
Sage DREAM7
challenge, game
announcement

49. PLAYER DEMOGRAPHICS

50. PHYLO

51. Players of Phylo compare the genome sequences of many animals to find genetic segments that are similar.
Mark Schrope PNAS 2013;110:7104-7106
©2013 by National Academy of Sciences

52. Figure 3. Statistics on the performance of players as a function of the number of sequence in the puzzle.
Kawrykow A, Roumanis G, Kam A, Kwak D, Leung C, et al. (2012) Phylo: A Citizen Science Approach for Improving Multiple Sequence
Alignment. PLoS ONE 7(3): e31362. doi:10.1371/journal.pone.0031362
http://127.0.0.1:8081/plosone/article?id=info:doi/10.1371/journal.pone.0031362

53. Open-Phylo crowd-computing system. (1) Scientists upload their sequences to the database, validate the alignment puzzles built by the
system (See green box in the data administration interface), or select new ones. (2) The same users monitor the progress of the crowd in
improving their alignments, close puzzles, open new puzzles and finally (3) download the best solutions. The crowd-computing engine is powered
by (a) many casual gamers playing classic puzzles and (b) a smaller number of experienced players, who have access to larger and more difficult
puzzles. Kwak et al. Genome Biology 2013 14:R116 doi:10.1186/gb-2013-14-10-r116
Open Phylo

54. Open Phylo
Performance of Open-Phylo using the casual or expert version of the Phylo video game. Ratio of puzzles improved by Open-Phylo for the scoring functions
Ancestor (top left), MUSCLE (top right), GUIDANCE (bottom right) and T-Coffee (bottom left). The alignment program used to calculate the initial MSAs is indicated
on the axis of the radar charts: Multiz (north), MUSCLE (west), PRANK (south) and T-Coffee (east). The area surrounded by a blue line corresponds to the
performance achieved with the casual puzzles only, while the area surrounded by a red line indicates the performance of the expert version only. The area
surrounded by a dashed green line shows the ratio of alignments improved by either the classic or expert version. Kwak et al. Genome Biology 2013 14:R116 doi:
10.1186/gb-2013-14-10-r116

55. Acknowledgments
● Ben Good for many interactions and slides (slides with black background):
http://fr.slideshare.net/goodb/serious-games-for-bioinformatics-education-ismb-2014-education-workshop
http://fr.slideshare.net/goodb/good-ben-rocky2013games
● Students a FDV who tested the use of games in class