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Tips for effective presentations

Ideas and practices that may help to deliver more understandable presentations

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Tips for effective presentations

  1. 1. Tips for effective presentations Dmytro Fishman (dmytro@ut.ee) Bioinformatics Research & Education Workshop (May 22, 2020 online)
  2. 2. www.slideshare.net/DimaFishman
  3. 3. Why would anyone care?
  4. 4. Gregor Mendel (1822 - 1884) In 1865 presents his work at several major venues but was not understood In 1868 elevated as a new abbot and quits his research career Mendel died in 1884 Several independent researchers rediscover Mendel’s laws in 1900 In 1863 starts growing common pea and discovers Laws of Inheritance
  5. 5. Gregor Mendel (1822 - 1884) In 1865 presents his work at several major venues but was not understood In 1863 starts growing common pea and discovers Laws of Inheritance Should he made a nice presentation “Father of modern genetics” Becomes a research super-star (while being alive) Genetics as we know it, is discovered earlier
  6. 6. What else presentations are good for?
  7. 7. Promoting organisation 400 000 000 iPod devices were sold
  8. 8. Photo is from https://i.ytimg.com/vi/Sm5xF-UYgdg/maxresdefault.jpg Educating His TED talk on Global Health has more than 11,400,000 views Hans Rosling
  9. 9. Try to get to know your audience before the talk
  10. 10. Try to tailor your talk to the audience Who are the people that I am going to talk to? What is their background & interests?
  11. 11. Background of the audience may determine the context of your talk Lecture for Data Scientists The same lecture for Social Scientists Trump supporter Hillary supporter Talk prepared once for one type of audience may not necessarily work for all future listeners
  12. 12. Make slides that guide your story
  13. 13. Make slides that guide your story Further explanation Talk so far
  14. 14. Make slides that guide your story
  15. 15. Make slides that guide your story Ease the cognitive load on your listeners by providing clues
  16. 16. Make slides that guide your story Ease the cognitive load on your listeners by providing clues Focus on one concept at a time
  17. 17. Protein Array Web ExploreR (PAWER) Dmytro Fishman, Ivan Kuzmin, Priit Adler, Jaak Vilo & Hedi Peterson
  18. 18. Enrichment analysis in GO:0005132 (9) type I interferon receptor binding 1.099x10-3 0 -log10(Padj)p-values ≤16 14 12 10 8 6 4 2 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins based on control proteins sample1.gpr sample2.gpr P sample3.gpr C sample4.gpr C sample5.gpr P sample6.gpr P CSV Metadata is added either … manually … … or via .csv file P C P C P C P C P C Clustering analysis in GPR files Samples are normalised Protein ID Gene name P-value T-statistic Differential proteins are identified List of proteins Normalised dataPAWER is linked to established tools to provide users with additional analysis
  19. 19. Focus on one concept at a time (do not show more than one new thing at a time) Initial slide Final slide
  20. 20. Protein Array Web ExploreR (PAWER) Dmytro Fishman, Ivan Kuzmin, Priit Adler, Jaak Vilo & Hedi Peterson
  21. 21. 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR GPR files
  22. 22. 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here GPR files (1)
  23. 23. 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins GPR files (1) (2)
  24. 24. 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins based on control proteins GPR files Samples are normalised (1) (2) (3)
  25. 25. 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins based on control proteins sample1.gpr sample2.gpr P sample3.gpr C sample4.gpr C sample5.gpr P sample6.gpr P CSV Metadata is added either … manually … … or via .csv file P C P C P C P C P C GPR files Samples are normalised (1) (2) (4) (3)
  26. 26. 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins based on control proteins sample1.gpr sample2.gpr P sample3.gpr C sample4.gpr C sample5.gpr P sample6.gpr P CSV Metadata is added either … manually … … or via .csv file P C P C P C P C P C GPR files Samples are normalised Protein ID Gene name P-value T-statistic Differential proteins are identified (1) (2) (4)(5) (3)
  27. 27. 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins based on control proteins sample1.gpr sample2.gpr P sample3.gpr C sample4.gpr C sample5.gpr P sample6.gpr P CSV Metadata is added either … manually … … or via .csv file P C P C P C P C P C GPR files Samples are normalised Protein ID Gene name P-value T-statistic Differential proteins are identified PAWER is linked to established tools to provide users with additional analysis (1) (2) (4)(5) (3)
  28. 28. Enrichment analysis in GO:0005132 (9) type I interferon receptor binding 1.099x10-3 0 -log10(Padj)p-values ≤16 14 12 10 8 6 4 2 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins based on control proteins sample1.gpr sample2.gpr P sample3.gpr C sample4.gpr C sample5.gpr P sample6.gpr P CSV Metadata is added either … manually … … or via .csv file P C P C P C P C P C GPR files Samples are normalised Protein ID Gene name P-value T-statistic Differential proteins are identified List of proteins PAWER is linked to established tools to provide users with additional analysis (1) (2) (4)(5) (3)
  29. 29. Enrichment analysis in GO:0005132 (9) type I interferon receptor binding 1.099x10-3 0 -log10(Padj)p-values ≤16 14 12 10 8 6 4 2 5 5 1 3 5 3 3 4 2 2 4 3 1 3 3 3 3 3 4 2 6 3 4 1 3 3 2 4 6 6 2 6 3 3 3 4 2 2 4 6 3 3 4 3 3 3 4 1 2 3 3 3 3 4 5 2 6 7 1 2 3 6 6 2 4 5 2 6 5 4 3 3 1 2 GPR Choose files to Upload Upload files to PAWER (https://biit.cs.ut.ee/pawer) or drag and drop GPR files here PAWER automatically detects foreground and background and chooses control proteins based on control proteins sample1.gpr sample2.gpr P sample3.gpr C sample4.gpr C sample5.gpr P sample6.gpr P CSV Metadata is added either … manually … … or via .csv file P C P C P C P C P C Clustering analysis in GPR files Samples are normalised Protein ID Gene name P-value T-statistic Differential proteins are identified List of proteins Normalised dataPAWER is linked to established tools to provide users with additional analysis (1) (2) (4)(5) (3)
  30. 30. Focus on one concept at a time (do not show more than one new thing at a time) Initial slide Initial slide Final slide
  31. 31. Focus on one concept at a time (do not show more than one new thing at a time) Initial slide Initial slide Final slide Final slide
  32. 32. Focus on one concept at a time (do not show more than one new thing at a time) Initial slide Initial slide Final slide Final slide
  33. 33. Give concrete examples
  34. 34. Give concrete examples Do not expect people to understand abstract ideas
  35. 35. y X independent variable dependentvariable Linear Regression
  36. 36. y X independent variable dependentvariable arg min = n ∑ i=1 ( − )2yi ̂yi We want to find a line such that … … it minimises the sum of errors Linear Regression
  37. 37. y X fareamount Linear Regression (example) distance 2 3 4 5 6 1 1 2 3 4 5
  38. 38. y X fareamount Linear Regression (example) distance 2 3 4 5 6 1 1 2 3 4 5 x y 1 2 2 4 3 5 4 4 5 5
  39. 39. y X fareamount Linear Regression (example) distance 2 3 4 5 6 1 1 2 3 4 5 x y x - x̄ y - ȳ (x - x̄ )2 (x - x̄ )(y - ȳ) 1 2 -2 -2 4 4 2 4 -1 0 1 0 3 5 0 1 0 0 4 4 1 0 1 0 5 5 2 1 4 2 x̄ = 3 ȳ = 4 2.2+=̂y 10 6 x0.6 w1 0.6 w0 = 2.2 = 2.2
  40. 40. Richard Feynman (1918 - 1988) In his autobiography “Surely you are joking, Mr. Feynman!” (1985), he wrote: “I can’t understand anything in general unless I’m carrying along in my mind a specific example and watching it go. Some people think in the beginning that I’m kind of slow and I don’t understand the problem…” Received a Nobel Prize in Physics in 1965
  41. 41. Make use of graphics!
  42. 42. y X 2 3 4 5 6 1 1 2 3 4 5 y X 2 3 4 5 6 1 1 2 3 4 5 y X 2 3 4 5 6 1 1 2 3 4 5 y X 2 3 4 5 6 1 1 2 3 4 5 to highlight the important bits Visualise as much as possible Use colour to differentiate Add shapes Mask irrelevant …
  43. 43. TACGGTATCAA ATCG TA A TGCCATAT TGTAG C T T TGT A G CAA AT C A T… T… Gene Making your own (in PowerPoint or Keynote)VS From https://images.app.goo.gl/ BvAceEiTgFE4iaHP6 Done in Keynote by myself 1. Quick and dirty 3. Can be hard to make it work with other slides 2. Conditions of use are not clear 1. Very time consuming to make 2. All rights reserved 3. Easy to integrate with the rest of the talk “Stealing” graphics from internet
  44. 44. OMICS Genomics (DNA) TACGGTATCAA ATCG TA A TGCCATAT TGTAGC T T TGT A G CAA AT C A T… T… Gene G UAU CAA A G UAU G CAUAUUGU A GUAUA Transcriptomics (RNA) Ribosome Amino Acids Proteomics (Proteins)Metabolomics (Metabolites)
  45. 45. TACGGTATCAA ATCG TA A TGCCATAT TGTAG C T T TGT A G CAA AT C A T… T… Gene “Stealing” graphics from internet Making your own (in PowerPoint or Keynote)VS From https://images.app.goo.gl/ BvAceEiTgFE4iaHP6 Done in Keynote by myself 1. Quick and dirty 3. Can be hard to make it work with other slides 2. Conditions of use are not clear 1. Very time consuming to make 2. All rights reserved 3. Easy to integrate with the rest of the talk
  46. 46. TACGGTATCAA ATCG TA A TGCCATAT TGTAG C T T TGT A G CAA AT C A T… T… Gene Making your own (in PowerPoint or Keynote) Done in Keynote by myself Maybe worth your time if you want to build your talk around it
  47. 47. From https://images.app.goo.gl/ BvAceEiTgFE4iaHP6 Makes sense if it is hard to visualise (and license is ok) “Stealing” graphics from internet
  48. 48. Create your own figures only to explain concepts not to visualise results (results images should be created automatically)
  49. 49. Practice!
  50. 50. Practice!Practice! (give a test talk to someone)
  51. 51. (give a test talk to someone) Teddy bear Your colleague Yourself Practice!
  52. 52. (give a test talk to someone) Teddy bear Your colleague Yourself Practice!
  53. 53. (give a test talk to someone) Teddy bear Your colleague Yourself Practice!
  54. 54. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback Appreciate their time & be open to their opinion (the closer they are to your target audience the better)
  55. 55. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback You should not agree to a pre-defence or test talk if you are not sure you will show courtesy
  56. 56. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback Appreciate their time & be open to their opinion (the closer they are to your target audience the better)
  57. 57. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback Appreciate their time & be open to their opinion (the closer they are to your target audience the better)
  58. 58. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback Appreciate their time & be open to their opinion (the closer they are to your target audience the better) Will not give your unbiased feedback about your talk, but may simulate third person perspective. Pronounce words that you will say during the talk to make it work.
  59. 59. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback External perspective External perspective Will not give your unbiased feedback about your talk, but may simulate third person perspective. Pronounce words that you will say during the talk to make it work. Appreciate their time & be open to their opinion (the closer they are to your target audience the better)
  60. 60. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback External perspective External perspective
  61. 61. (give a test talk to someone) Teddy bear Your colleague Yourself Practice! Feedback External perspective External perspective If you could remember only one thing from my talk, this should be the one
  62. 62. Before your talk check the equipment
  63. 63. Is projector working? Computer is not going to update itself? Test the recording Can you change the slides? Does your mic work? Before your talk check the equipment
  64. 64. http://researchinprogress.tumblr.com/ Check the equipment before things got messy…
  65. 65. Give credit where credit is due
  66. 66. Give credit where credit is due
  67. 67. If you present joint work always acknowledge your co-authors Give credit where credit is due
  68. 68. Give credit where credit is due
  69. 69. If you present work done in a larger project, acknowledge your team mates Give credit where credit is due
  70. 70. Give credit where credit is due
  71. 71. It is not only co- authors who contributed
  72. 72. It is not only co- authors who contributed
  73. 73. Give credit where credit is due
  74. 74. Give credit where credit is due Audience are not only people you should try to make feel good with your talk
  75. 75. Best practices (summary)
  76. 76. Best practices (summary) 0 TACGGTATCAA ATCG TA A TG CCATAT TGTAG C T T TGT A G CAA AT C A T… T… Check the equipment Give credit! Results should be visualised automatically Practice! Visualise difficult concepts Give examples Your slides should guide your talk Makes sense to tailor your talk to your audience Good talks may help to disseminate your science
  77. 77. Good talks may help to disseminate your science If you do everything correctly expect to receive a lot of questions 0 Makes sense to tailor your talk to your audience Your slides should guide your talk Practice! Give examples TACGGTATCAA ATCG TA A TG CCATAT TGTAG C T T TGT A G CAA AT C A T… T… Visualise difficult conceptsCheck the equipment Give credit! Results should be visualised automatically
  78. 78. Good talks may help to disseminate your science If you do everything correctly expect to receive a lot of questions 0 Makes sense to tailor your talk to your audience Your slides should guide your talk Practice! Give examples TACGGTATCAA ATCG TA A TG CCATAT TGTAG C T T TGT A G CAA AT C A T… T… Visualise difficult conceptsCheck the equipment Give credit! Results should be visualised automatically More questions I get, more understandable it was
  79. 79. https://biit.cs.ut.ee/ Thank you!
  80. 80. www.slideshare.net/DimaFishman

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