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Data Mining データ・マイニング

Data Mining データ・マイニング. 2014/07/14 Unit Statistical Genetics Ryo Yamada 統計遺伝学 分野 山田　亮. A blank sheet for you to answer Qs during the class , that is collected at the end of class . Put your name and lab on the top. 何 も書いていない紙は講義中の質問への回答を書くためのものです。 講義終了時、回収。 名前と所属を用紙の一番上に書きなさい。.

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Data Mining データ・マイニング

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  1. Data Miningデータ・マイニング 2014/07/14 Unit Statistical Genetics Ryo Yamada 統計遺伝学分野 山田　亮

  2. A blank sheet for you to answer Qs during the class,that is collected at the end of class.Put your name and lab on the top.何も書いていない紙は講義中の質問への回答を書くためのものです。講義終了時、回収。名前と所属を用紙の一番上に書きなさい。

  3. Glomerulus腎糸球体Q “Sketch スケッチせよ”

  4. Model モデルQ2 “Sketch スケッチせよ”

  5. QDifference between the photo and the diagram?写真と模式図の違いは？ • Write your opinion. 意見を書け

  6. The diagramkeeps/stressessomething and throw awaysomething in the photo. 模式図は写真にある何かを取り出し、何かを捨てている

  7. QDifference between PRE-filter and POST-filter?フィルタリング前後での違いは？ • Write your opinion. 意見を書け

  8. QThere are three 2-D images.What are lost?２次元投影図が３枚ある。何が失われている？ • Write your opinion. 意見を書け

  9. Figure 2. Correlation between age of females and parturition date. Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

  10. Figure 2. Correlation between age of females and parturition date. Q What is this about? What are taken out and what are thrown away? Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

  11. Figure 2. Correlation between age of females and parturition date. Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

  12. Figure 1. Seasonal variation in offspring sex ratio. Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

  13. Figure 1. Seasonal variation in offspring sex ratio. Q What is this about? What are taken out and what are thrown away? Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

  14. Figure 1. Seasonal variation in offspring sex ratio. Barclay RMR (2012) Variable Variation: Annual and Seasonal Changes in Offspring Sex Ratio in a Bat. PLoS ONE 7(5): e36344. doi:10.1371/journal.pone.0036344 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036344

  15. 5′- and 3′-end distributions (TSB). 5′ and 3′ ends within the limits of recessing <300 nt and protruding <1,000 nt from their corresponding annotated ORFs were plotted as histograms. Høvik H et al. J. Bacteriol. 2012;194:100-114

  16. 5′- and 3′-end distributions (TSB). 5′ and 3′ ends within the limits of recessing <300 nt and protruding <1,000 nt from their corresponding annotated ORFs were plotted as histograms. Q What is this about? What are taken out and what are thrown away? Høvik H et al. J. Bacteriol. 2012;194:100-114

  17. 5′- and 3′-end distributions (TSB). 5′ and 3′ ends within the limits of recessing <300 nt and protruding <1,000 nt from their corresponding annotated ORFs were plotted as histograms. Høvik H et al. J. Bacteriol. 2012;194:100-114

  18. Figure 4. Scatter plot of age versus biomarker summary score for men and women from the Estonian Biobank cohort. Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

  19. Figure 4. Scatter plot of age versus biomarker summary score for men and women from the Estonian Biobank cohort. Q What is this about? What are taken out and what are thrown away? Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

  20. Figure 4. Scatter plot of age versus biomarker summary score for men and women from the Estonian Biobank cohort. Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

  21. Figure 5. Cumulative probability of death in the Estonian Biobank cohort by percentiles of the biomarker summary score. Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

  22. Figure 6. Discrimination curves for 5-y mortality in FINRISK cohort. Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

  23. Figure 6. Discrimination curves for 5-y mortality in FINRISK cohort. Q What is this about? What are taken out and what are thrown away? Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

  24. Figure 6. Discrimination curves for 5-y mortality in FINRISK cohort. Fischer K, Kettunen J, Würtz P, Haller T, et al. (2014) Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons. PLoS Med 11(2): e1001606. doi:10.1371/journal.pmed.1001606 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001606

  25. Figure 1. Odds ratio of death for transfusion compared to no transfusion by risk category. Perel P, Clayton T, Altman DG, Croft P, et al. (2014) Red Blood Cell Transfusion and Mortality in Trauma Patients: Risk-Stratified Analysis of an Observational Study. PLoS Med 11(6): e1001664. doi:10.1371/journal.pmed.1001664 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001664

  26. Figure 1. Odds ratio of death for transfusion compared to no transfusion by risk category. Q What is this about? What are taken out and what are thrown away? Perel P, Clayton T, Altman DG, Croft P, et al. (2014) Red Blood Cell Transfusion and Mortality in Trauma Patients: Risk-Stratified Analysis of an Observational Study. PLoS Med 11(6): e1001664. doi:10.1371/journal.pmed.1001664 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001664

  27. Figure 1. Odds ratio of death for transfusion compared to no transfusion by risk category. Perel P, Clayton T, Altman DG, Croft P, et al. (2014) Red Blood Cell Transfusion and Mortality in Trauma Patients: Risk-Stratified Analysis of an Observational Study. PLoS Med 11(6): e1001664. doi:10.1371/journal.pmed.1001664 http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001664

  28. Figure 3. Time courses of RT-related activation in representative gray matter ROIs. Yarkoni T, Barch DM, Gray JR, Conturo TE, et al. (2009) BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis. PLoS ONE 4(1): e4257. doi:10.1371/journal.pone.0004257 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004257

  29. Figure 3. Time courses of RT-related activation in representative gray matter ROIs. Q7 What is this about? What are taken out and what are thrown away? Yarkoni T, Barch DM, Gray JR, Conturo TE, et al. (2009) BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis. PLoS ONE 4(1): e4257. doi:10.1371/journal.pone.0004257 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004257

  30. Figure 3. Time courses of RT-related activation in representative gray matter ROIs. Yarkoni T, Barch DM, Gray JR, Conturo TE, et al. (2009) BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis. PLoS ONE 4(1): e4257. doi:10.1371/journal.pone.0004257 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004257

  31. Figure 1. Network Illustrating Structural Parameters. Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  32. Figure 1. Network Illustrating Structural Parameters. Q8 What is this about? What are taken out and what are thrown away? Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  33. Figure 1. Network Illustrating Structural Parameters. Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  34. Figure 3. Empirical differences in flu contagion between “friend” group and randomly chosen individuals. Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  35. Figure 3. Empirical differences in flu contagion between “friend” group and randomly chosen individuals. Q9 What is this about? What are taken out and what are thrown away? Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  36. Figure 3. Empirical differences in flu contagion between “friend” group and randomly chosen individuals. Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  37. Circular transcriptome map showing the normalized RNAseq transcription signals derived from the MIN-cultured cells. Høvik H et al. J. Bacteriol. 2012;194:100-114

  38. Circular transcriptome map showing the normalized RNAseq transcription signals derived from the MIN-cultured cells. Q What is this about? How do you summarize these? Høvik H et al. J. Bacteriol. 2012;194:100-114

  39. Circular transcriptome map showing the normalized RNAseq transcription signals derived from the MIN-cultured cells. Høvik H et al. J. Bacteriol. 2012;194:100-114

  40. Figure 4. Progression of flu contagion in the friendship network over time. Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  41. Figure 4. Progression of flu contagion in the friendship network over time. Q What is this about? How do you summarize these? Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  42. Figure 4. Progression of flu contagion in the friendship network over time. Christakis NA, Fowler JH (2010) Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE 5(9): e12948. doi:10.1371/journal.pone.0012948 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012948

  43. Q What is this about? What are taken out and what are thrown away?

  44. Q What is this about? How do you summarize these?

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