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BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
BU - Wellesely iGEM 2011 World Finals
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BU - Wellesely iGEM 2011 World Finals

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  • 1. Challenges data designdeployment trial & error time management debugging iterative design complexity manual error standardization sharing automation integration specification high throughput initial research verification speed accuracy
  • 2. Apply engineering principles to synthetic biology by utilizing user-centered design to build software tools that foster collaborative problem solving, support complex system design, and enable automation in the lab. BU-Wellesley Software 2011 Our Vision
  • 3. Workflow BU-Wellesley Software 2011
  • 4. User Centered Design BU-Wellesley Software 2011
  • 5. Preliminary User Studies Position # PIs 9 Postdocs 6 Industry Researchers 2 Student Researchers 12 Research Assistant 2 Master Student 1 Total 32 Goal Design requirements for synthetic biologists Interview Procedure 1 hour interviews in laboratories Interview Questions  Procedure walk-through  Research goals  Work practices  Computational tools  Future of the field Data collection  Video  Voice recordings  Screenshots  Observations Qualitative Methods • Affinity diagrams • Iterative coding Institutions • Boston University • Harvard Medical School • MIT • WellesleyCollege • Wyss Institute
  • 6. Findings: User Study Results BU -Wellesley Software
  • 7. Findings: User Study Results Alleviate Data Explosion IntegrateWorkflow Provide Multiple Forms of Evidence Support from Novice to Expert Facilitate Collaboration BU-Wellesley Software 2011
  • 8. Findings: User Study Results Alleviate Data Explosion IntegrateWorkflow Provide Multiple Forms of Evidence Support from Novice to Expert Facilitate Collaboration BU-Wellesley Software 2011
  • 9. “ ” By taking into account the collaborative process, tabletop software can help novices learn from experts, making an invaluable impact on synthetic biology -Natalie Kuldell, SynBERC
  • 10. BU-Wellesley Software 2011 Optimus Primer Multiplatform collaborative primer designer Facilitates transition from novice to expert
  • 11. Teaching Primer Design BU-Wellesley Software 2011
  • 12. Low-Fidelity Prototype BU-Wellesley Software 2011
  • 13. G-nome Surfer Pro & Optimus Primer BU-Wellesley Software 2011
  • 14. Evaluation BU-Wellesley Software 2011 1.Usability of concrete interaction techniques 12 users 2.Usefulness for collaborative learning 20 users 3. Impact of an end-to-end solution iGEM 2012 wet lab team Advanced Biology seminar inWellesley College
  • 15. Evaluating Usefulness BU-Wellesley Software 2011 Intermediate College-level Neuroscience Lab & Synthetic Biology Lab at BU
  • 16. Results 0 1 2 3 4 5 6 7 MentalDemand PhysicalDemand TemporalDemand Performance Confidence Effort Complexity Difficulty Enjoyment Frustration Score NASATLX & Engagement 0 1 2 3 4 5 MutualUnderstanding Dialogue InfoPooling ReachingConsensus TaskDivision TimeManagement ReciprocateInteractions IndividualTaskOrientation Score Collaborative Learning
  • 17. G-nome Surfer Pro reduces subjective workload, improves collaboration, encourages reflection, and facilitates intuitive interaction. Findings BU-Wellesley Software 2011
  • 18. Using Gnome Surfer in the Lab Gnome Surfer Pro Pubmed research onTuberculosis Gene selection fromTB genome Sequence analysis Tuberculosis Genes Rv2324 Rv3574 Rv3574 promoter Rv0324 Other genes Smeg6038 Smeg6042 Cre Dre Flp
  • 19. Designing Primers Optimus Primer Designed primers to amplifyTB genes and generate BioBricks A subset of our primers is listed below Genes Forward Primers Reverse Primers RV2324 CGGCCGCTTCTAGATGGACCGCCTGGATGACACC CGGCCTACTAGTACTAGGGCGGCATGCGGTCG Smeg6038 CGCCCGCTTCTAGAGCGGGGTGACCCTTTCTCTTC CCGCTACTAGTATGAATTGCCTCCCGGATCG RV3574 GGCCGCTTCTAGAGCTTGCAGACCTCCGCGTCGA GGCCGCTACTAGTATTTCATGACCGCGCGAGGTG RV0324 CGCGCGCTTCTAGATGGCTGGACAGTCCGATCG CGCCTGTAGATTCGCCGATGCCGTGGATA RV3574 CGCCCGCTTCTAGATGGCGGTACTTGCCGAGTC TCGATGCGGCTGAACTCCCGACCCAGCGCCGAC Smeg_6042 CGCGCTTCTAGATGACCAACGTGGCGGTTCTC CGATGCGTTCGAACTCGCGTCCGAGTGCCGAG
  • 20. BU-Wellesley Software 2011 Synbio: General outlook • Biology is... • Want to investigate complex interactions between genes • Avoid large number of constructs • Create sophisticated genetic circuits • Generate a large state space
  • 21. BU-Wellesley Software 2011 Trumpet: Configurable constructs • Can we build a configurable biological construct? • Prior work • Ham et al. five-state machine (2009) • Friedland et al. three-state counter (2008) • Our goal: a fully permutable construct • Results: • Two algorithms for designing such constructs
  • 22. Part Part Invertase BU-Wellesley Software 2011 Invertases
  • 23. Trumpet: Configurable constructs • Two design algorithms: • Pancake and Linksort • Pancake operations • Bring to head (BtH) • Push into place (PiP) • Complexity • invertases, operations • Implemented with nested invertase sites • BtH: One site per part • PiP: N sites per part
  • 24. Trumpet generated designs BU-Wellesley Software 2011 Link Sort Pancake
  • 25. BU-Wellesley Software 2011 Trumpet Trumpet produces a permutable design using invertases
  • 26. Trumpet BU-Wellesley Software 2011
  • 27. Invertase –sites Flp – frt Dre – rox Cre – lox Trumpet Generated a reconfigurable circuit with 2TB genes and 3 invertase sites Generating a Circuit Design with Trumpet
  • 28. PuppetShow: • 10 part BioBrick using current software: •200 lines of code • 10 part Biobrickusing PuppetShow: •~ 20 lines BU-Wellesley Software 2011 Define protocols  Call function Robot moves
  • 29. PuppetShow: features BU-Wellesley Software 2011 • Define protocols and assembly programs • Generates Puppeteer code automatically • Optimizes labware allocation • Saves samples and protocol history to database • Maintains Puppeteer Protocol Repository
  • 30. BU-Wellesley Software 2011 PuppetShow: Workflow Spec Plan Protocol Macro Instruction Action Robot #1 Ligation volume: 17µL Colonies: 300+ Robot #2 Ligation volume: 16.7µL Colonies: 300+ Manual Side-by- Side Ligation Volume: 20µL Colonies: 300+
  • 31. eLabNotebook BU-Wellesley Software 2011
  • 32. PuppetShow & eLabNotebook BU-Wellesley Software 2011
  • 33. Assembling DNA with PuppetShow Puppet Show Run protocols for the DNA assembly of the genetic circuit using a liquid handling robot Manual LabWork Do the protocols manually to build the genetic circuit M: MW Ladder 1: Uncut BioBrick 2: Manual trial 3-5: Robot trials
  • 34. Future Work & Conclusion BU-Wellesley Software 2011
  • 35. Impact • Feasible to streamline experimental process through a suite of tools • Facilitates collaborative learning support of novice users • Developed and automated 2 different algorithms which place invertase sites through Clotho. • Created user-friendly interface for automating protocols to a robot • Successfully tested in the wet lab BU-Wellesley Software 2011 The user interface is limiting in many fields. Designing software for synthetic biology with collaborative and educational capabilities will help attract new blood to the field and provide those in the field with vital new design perspectives. -George M. Church, Harvard Medical School “ ”
  • 36. Acknowledgements BU: Daniel Dwyer, Jim Collins, and the Collins Lab, Andrew Krueger, James Galagan, and the Galagan Lab, Gretchen Fougere, Assistant Dean of Outreach and Diversity BBNTechnologies: Aaron Aadler JBEI: Josh Gilmore JHU: Jef Boeke, NoahYoung MIT: Jonathan Babb and theWeiss Lab,Tiffany Huang, Louis Lamia and the MIT iGEMTeam, Joy, Leanna, Paul, Shawn, and Shirley of the MIT iGEM team of 2010 Somerville High School: Chris Angelli UC Berkeley: J. Christopher Anderson WellesleyCollege: Catherine Summa,Wellesley College ScienceCenter Summer Research,Yui Suzuki and the Suzuki Lab Wyss Institute: Avi Robinson-Mosher
  • 37. Surface Strengths • Facilitates collaboration • Promotes hands-on learning • Education • Tangible interface facilitates spatial organization of information • Interface geared for novice researchers Weaknesses • Low-resolution display limits visualization capabilities • Expensive • Large footprint BU-Wellesley Software 2011
  • 38. Evaluating Problem Solving • Quantitative measures – Number and value of insights – time per activity – subjective workload – attitude – physical and verbal participation – equality of participation • Qualitative indicators – collaboration style – problem-solving strategy – nature of discussion BU-Wellesley Software 2011
  • 39. Feedback from Users BU-Wellesley Software 2011 Our discussions were able to get further with the help of the G-nome Surfer. G-nome Surfer contributed most to my satisfaction because while I usually prefer to work alone, the teamwork felt effortless, natural, and fun. G-nome Surfer really helped in examining the strengths and weaknesses of your own hypothesis with those of others in the group. Being able to see and compare researched data side-by-side was particularly useful. It was very helpful in the sense that information was very easy to find and could be organized into places that are easily seen and used.
  • 40. G-nome Surfer vs GSP BU-Wellesley Software 2011

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