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Data Visualization in Biomedical Sciences: More than Meets the Eye
The document discusses the significance of data visualization in biomedical sciences, highlighting its role in aiding researchers, decision makers, and the public in understanding complex data. It addresses the reproducibility crisis in science, emphasizing how effective visualization can help in hypothesis generation, exploration, and storytelling. The author presents various visualization methods and tools to improve insight and facilitate data-driven discoveries.
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Data Visualization in Biomedical Sciences: More than Meets the Eye
- 1. Data Visualization inBiomedical Sciences: More than Meets the Eye Nils Gehlenborg, PhD Department of Biomedical Informatics Harvard Medical School http://gehlenborglab.org @ngehlenborghttp://gehlenborglab.org
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- 4. Data Visualization inBiomedical Sciences: More than Meets the Eye Nils Gehlenborg, PhD Department of Biomedical Informatics Harvard Medical School http://gehlenborglab.org @ngehlenborghttp://gehlenborglab.org
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- 7. http://gehlenborglab.org Research Data ClinicalData Casual Users Expert Users
- 8. http://gehlenborglab.org Clinical Data Casual Users ExpertUsers Research Data
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- 18. Researchers Researchers Decision Makers PolicyMakers Citizens … Insight EXPLORATION EXPLANATION Decision Makers Policy Makers Citizens …
- 19. Researchers Researchers Decision Makers PolicyMakers Citizens … Insight EXPLORATION EXPLANATION Decision Makers Policy Makers Citizens …
- 20. Researchers Researchers Decision Makers PolicyMakers Citizens … Insight EXPLORATION EXPLANATION Decision Makers Policy Makers Citizens …
- 21. WHY SHOULD WECARE?
- 22. Nature asked 1,576researchers if there is a reproducibility crisis in science. M Baker, Nature 533, 452-454, 2016
- 23. 0% 100% No crisis(3%) Don’t know (7%) Slight crisis (38%) M Baker, Nature 533, 452-454, 2016 Significant crisis (52%) Nature asked 1,576 researchers if there is a reproducibility crisis in science.
- 24. M Baker, Nature533, 452-454, 2016
- 25. M Baker, Nature533, 452-454, 2016
- 26. M Baker, Nature533, 452-454, 2016
- 27. Intentional? Inability to captureeverything? Inability to communicate everything? M Baker, Nature 533, 452-454, 2016
- 28. Intentional? Inability to captureeverything? Inability to communicate everything? SOCIAL ISSUE TECHNICAL ISSUES M Baker, Nature 533, 452-454, 2016
- 29. HOW IS THISRELATED TO DATA VISUALIZATION?
- 30. Tumor Subtypes PROBLEM 1 Visualizeoverlap of patient sets across two or more stratifications. PROBLEM 2 Visualize characteristics of patient sets within a stratification of interest.
- 31. M Streit, A Lex, S Gratzl, C Partl, D Schmalstieg, H Pfister, PPark, N Gehlenborg , Nature Methods (2014) StratomeX
- 33. Tumor Subtypes PROBLEM 1 Visualizeoverlap of patient sets across two or more stratifications. PROBLEM 2 Visualize characteristics of patient sets within a stratification of interest. PROBLEM 3 Identify relevant stratifications, pathways, and clinical variables.
- 34. Is there amutation that overlaps with this mRNA cluster? Is there a CNV that affects survival? Is there a pathway that is enriched in this cluster? Is there a mutually exclusive mutation? Query Stratifications Clinical Params Pathways Guided Exploration M Streit, A Lex, S Gratzl, C Partl, D Schmalstieg, H Pfister, P Park, N Gehlenborg , Nature Methods (2014)
- 35. Query Rank Visualize Stratifications Clinical Params Pathways Guided Exploration M Streit, A Lex, S Gratzl, C Partl, D Schmalstieg, H Pfister,P Park, N Gehlenborg , Nature Methods (2014)
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- 44. finding figure/videoAuthoringExploration Presentation DATA-DRIVENCOMMUNICATION finding figure/videoAuthoringExploration Presentation Current Model DATA-DRIVEN DISCOVERY
- 45. DATA-DRIVEN COMMUNICATION finding figure/videoAuthoringPresentation What we show. DATA-DRIVEN DISCOVERY
- 46. DATA-DRIVEN COMMUNICATION finding figure/videoAuthoringPresentation What we tell. DATA-DRIVEN DISCOVERY
- 47. DATA-DRIVEN COMMUNICATION finding figure/videoAuthoringPresentation What we did. DATA-DRIVEN DISCOVERY
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- 49. DATA-DRIVEN COMMUNICATION track provenance annotateobservations make sense of observations tell the story DATA-DRIVEN DISCOVERY
- 50. DATA-DRIVEN COMMUNICATION Capture Label Understand Explain track provenance annotateobservations make sense of observations tell the story C L U E DATA-DRIVEN DISCOVERY
- 51. CLUE vistories Authoring Exploration Presentation CLUE Model DATA-DRIVENCOMMUNICATION DATA-DRIVEN DISCOVERY
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- 60. VISTORY = visualization+ story + history Do collaborative data analysis. Use during peer-review. Publish with a paper. Embed in a presentation.
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- 63. DATA-DRIVEN DISCOVERY DATA-DRIVEN COMMUNICATION http://vistories.org SAMUELGRATZL ALEXANDER LEX MARC STREIT
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