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* [[Media:On_being_scientist_2009.pdf|On being a scientist]] - On being a scientist article | * [[Media:On_being_scientist_2009.pdf|On being a scientist]] - On being a scientist article | ||
* [[Media:On+Being+A+Scientist.pptx|On being a scientist ppt]] - On being a scientist slides | * [[Media:On+Being+A+Scientist.pptx|On being a scientist ppt]] - On being a scientist slides | ||
+ | =====Recorded Lectures===== | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=58d266f3-210d-4d7c-8788-aa6f014a70ec Cluster computing] - Dan Barker | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=65fd73f4-195a-4198-87b7-aa6f01299c4c RCRS Training] - Mukherjee | ||
==== Day 2: Reproducible Research, Study Design and Inference, and Linear Regression, June 18 ==== | ==== Day 2: Reproducible Research, Study Design and Inference, and Linear Regression, June 18 ==== | ||
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* [[Media: LinearRegression-2019slides.pdf|Linear regression]] Hector | * [[Media: LinearRegression-2019slides.pdf|Linear regression]] Hector | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=82eb9256-bf4c-40a4-8487-aa7000d6d63b Reproducible research] - LeFaive |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=4c63a289-5f6a-4706-8627-aa7000f2900e Study designs & Inference] - Little | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=44357ae0-d327-461e-a386-aa70014ddbb0 Linear regression] - Hector | ||
==== Day 3: Logistic Regression, Observational Data and Bias, and Probability, June 19 ==== | ==== Day 3: Logistic Regression, Observational Data and Bias, and Probability, June 19 ==== | ||
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* [[Media:Probability_Rmd.pdf |Probability]] - Hartman | * [[Media:Probability_Rmd.pdf |Probability]] - Hartman | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=1d0dd55a-3464-4a16-b9b5-aa7100d6b216 Logistic regression] - Hector |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=bbdbb94d-6455-4e3d-a0a3-aa7100f2fec2 Observational Data, Bias] - Little | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=a111bacf-7bde-4376-9738-aa71014ebdf6 Probability review] - Hartman | ||
==== Day 4: Causal inference, Parameter Estimation/Likelihood, and Linear Algebra, June 20 ==== | ==== Day 4: Causal inference, Parameter Estimation/Likelihood, and Linear Algebra, June 20 ==== | ||
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*[[Media: Linear_algebra.pdf|Linear algebra]] - Hartman | *[[Media: Linear_algebra.pdf|Linear algebra]] - Hartman | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=b9a2f7e1-a2d2-400f-aaf3-aa7200d78be4 Causal Inference] - Wu |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=cd4dba3d-a4dc-4972-bbe8-aa7200f30723 Parameter Estimation / Likelihood] - Little | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=0a05bea8-c048-4d52-b193-aa72014f8220 Linear Algebra] - Hartman | ||
==== Day 5: Data Wrangling in R with dplyr, Parts I and II, June 21 ==== | ==== Day 5: Data Wrangling in R with dplyr, Parts I and II, June 21 ==== | ||
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*[[Media: Boehnke_Journey_BDSI2019.pptx|Journey lectures]] - Boehnke | *[[Media: Boehnke_Journey_BDSI2019.pptx|Journey lectures]] - Boehnke | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=d3e590db-bfe9-4ab5-91b1-aa7300f2ee1f R Workshop dplyr Part II] - Flickinger |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=399865c6-35b3-4eb1-8f36-aa73010fd4ba Journey Lecture] - Boehnke | ||
+ | * No Recording Available (Data Wrangling in R with dplyr - Flickinger) | ||
=== <u>Week 2</u> === | === <u>Week 2</u> === | ||
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*[[Media: Bdsi_2019_r_practice_ggplot2_nycflights_answers.pdf|Ggplot2 flights answers exercise]] - Flickinger | *[[Media: Bdsi_2019_r_practice_ggplot2_nycflights_answers.pdf|Ggplot2 flights answers exercise]] - Flickinger | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=4e2adcbb-ae95-454b-a23f-aa7600d69323 Visualizing Data in R Part I] - Flickinger |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=d3e2760c-619b-47b7-8eb3-aa7600efc305 Visualizing Data in R - Part II] - Flickinger | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=39a14a1a-4958-49bb-bee2-aa76014dc1da Generalized Linear Models] - Hartman | ||
==== Day 7: Machine Learning I & Model Selection, June 25 ==== | ==== Day 7: Machine Learning I & Model Selection, June 25 ==== | ||
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*[[Media: Wiens_ML_Lecture1.pdf|Machine Learning I slides]] - Wiens | *[[Media: Wiens_ML_Lecture1.pdf|Machine Learning I slides]] - Wiens | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=37a6279a-2657-49bb-b5f8-aa7700f31d9d Model Selection 1] - Beesley |
+ | *No recording available (Machine Learning I - Wiens) | ||
==== Day 8: Machine Learning II & Unsupervised Learning/Clustering I, June 26 ==== | ==== Day 8: Machine Learning II & Unsupervised Learning/Clustering I, June 26 ==== | ||
*[[Media: Wiens_ML_Lecture2.pdf|Machine Learning II slides]] - Wiens | *[[Media: Wiens_ML_Lecture2.pdf|Machine Learning II slides]] - Wiens | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=699e8e7c-a33a-4efb-9f90-aa78014dfeda Correlated data models] - Hartman |
+ | *No recording available (Machine Learning II - Wiens) | ||
+ | *No recording available (Unsupervised Learning, Clustering I - Koutra) | ||
==== Day 9: Unsupervised Learning/Clustering II and Model Selection II, June 27 ==== | ==== Day 9: Unsupervised Learning/Clustering II and Model Selection II, June 27 ==== | ||
− | * | + | *[[Media:beesley ms2.pdf|Model Selection II slides]] - Beesley |
+ | =====Recorded Lectures===== | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=1f07dda4-81d9-41b0-bd43-aa7900f30d9e Model Selection Part II] - Beesley | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=84588ff1-9cf8-4f44-b1f4-aa79014de845 Assessment of predictive models] - Boonstra | ||
+ | * No recording available (Unsupervised Learning, Clustering II - Koutra) | ||
==== Day 10: Python Workshop I and II, June 28 ==== | ==== Day 10: Python Workshop I and II, June 28 ==== | ||
*[[Media:BDSI Python Tutorial.pdf|Python Workshop I and II]] - Kamran | *[[Media:BDSI Python Tutorial.pdf|Python Workshop I and II]] - Kamran | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=d0134ee0-6ba2-4f4c-be10-aa7a00d74e9c Python Workshop] - Kamran |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=e194044c-b797-4a55-b7b1-aa7a00f30604 Python workshop Part II] - Kamran | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8aa9d6ab-7c78-4eb7-8a46-aa7a0113714d Journey Lecture] - Banerjee | ||
=== <u>Week 3</u> === | === <u>Week 3</u> === | ||
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*[[Media:bdsi2019-vis-for-data-science-1.pdf|Visualization I slides]] - Kay | *[[Media:bdsi2019-vis-for-data-science-1.pdf|Visualization I slides]] - Kay | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=56ea7d1a-d2df-4d2c-a570-aa7d00d6b518 Data Mining Part I] - Gryak |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=da78299d-aecf-4823-bc5f-aa7d00f39f4b Visualization I] - Kay | ||
==== Day 12: Data Mining II and Precision Health, July 2 ==== | ==== Day 12: Data Mining II and Precision Health, July 2 ==== | ||
*[[Media:ClinicalCareMachineLearningBDSI.pptx|Precision Health slides]] - Kheterpal | *[[Media:ClinicalCareMachineLearningBDSI.pptx|Precision Health slides]] - Kheterpal | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=393e57a1-b764-49c0-9a77-aa7e00f21944 Precision Health] - Kheterpal |
+ | * No recording available (Data Mining II - Gryak) | ||
==== Day 13: Visualization II and Intro to Bayes I, July 3==== | ==== Day 13: Visualization II and Intro to Bayes I, July 3==== | ||
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*[[Media:Bayes1.pdf|Intro to Bayes I slides]] - Wen | *[[Media:Bayes1.pdf|Intro to Bayes I slides]] - Wen | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=91c1bb99-5542-4086-8389-aa7f00f2dab8 Introduction to Bayes] - Wen |
+ | * No recording available (Visualization II - Kay) | ||
==== Day 14: July 4 - NO CLASS ==== | ==== Day 14: July 4 - NO CLASS ==== | ||
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*[[Media:Bayes2.pdf|Intro to Bayes II slides]] - Wen | *[[Media:Bayes2.pdf|Intro to Bayes II slides]] - Wen | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=279b3f8e-deed-4086-bfab-aa81010fb121 Journey lecture] - Panigrahi |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=ded3c71e-7fd3-4b76-a3a5-aa8100d649e9 Introduction to Bayes II] - Wen | ||
+ | * No recording available (Journey Lectures: Taylor) | ||
+ | * No recording available (State of the Institute: Mukherjee) | ||
=== <u>Week 4</u> === | === <u>Week 4</u> === | ||
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*[[Media:BigDataSummerInstitute_Surakka-1.pptx|From Genomics to Prevention of Cardiovascular Diseases slides]] - Surakka | *[[Media:BigDataSummerInstitute_Surakka-1.pptx|From Genomics to Prevention of Cardiovascular Diseases slides]] - Surakka | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=2f15f9f3-55e5-4450-b562-aa8400d70030 Genomics to Prevention of Cardiovascular Disease] - Surakka |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=285e928a-cf75-49ce-8440-aa8400f3056d R Markdown] - Boonstra | ||
==== Day 17: Bayes Computation I and II, July 9 ==== | ==== Day 17: Bayes Computation I and II, July 9 ==== | ||
*[[Media:BDSI_Lecture_Slides.pdf|Bayes Computation I and II slides]] - Chen | *[[Media:BDSI_Lecture_Slides.pdf|Bayes Computation I and II slides]] - Chen | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *No recordings available (Computation I & II - Chen) |
==== Day 18: Reading Like a Scientific Writer and Social Network, July 10 ==== | ==== Day 18: Reading Like a Scientific Writer and Social Network, July 10 ==== | ||
*[[Media:Griffiths-BDSI-Reading like a Scientific Writer-2019.pptx|Reading Like a Scientific Writer slides]] - Griffiths | *[[Media:Griffiths-BDSI-Reading like a Scientific Writer-2019.pptx|Reading Like a Scientific Writer slides]] - Griffiths | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | * No recording available (Reading like a scientific writer - Griffiths) |
+ | * No recording available (Social Network - Adar) | ||
+ | * No recording available (Journey Lecture-Bowman) | ||
==== Day 19: Stroke Disparities and Human-Centered Computing: Using Speech to Understand Behavior, July 11 ==== | ==== Day 19: Stroke Disparities and Human-Centered Computing: Using Speech to Understand Behavior, July 11 ==== | ||
*[[Media:Stroke health Disparities Program final 2019-1.pptx|Stroke Disparities slides]] - Lisabeth | *[[Media:Stroke health Disparities Program final 2019-1.pptx|Stroke Disparities slides]] - Lisabeth | ||
*[[Media:EMP_BDSI.pdf|Human-Centered Computing slides]] - Provost | *[[Media:EMP_BDSI.pdf|Human-Centered Computing slides]] - Provost | ||
+ | =====Recorded Lectures===== | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=96a45868-6793-4579-be17-aa8700d6d01f Stroke disparities] - Lisabeth | ||
+ | * No recording available (Human-Centered Computing: Using Speech to Understand Behavior - Provost) | ||
==== Day 20: Spatial Epidemiology, July 12 ==== | ==== Day 20: Spatial Epidemiology, July 12 ==== | ||
*[[Media:zelner_bdsi.pdf|Spatial Epidemiology slides]] - Zelner | *[[Media:zelner_bdsi.pdf|Spatial Epidemiology slides]] - Zelner | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=0f0408ed-8286-4412-8cfc-aa88010ed154 Journey Lecture] - Spino |
+ | * No recording available (Spatial Epidemiology - Zelner) | ||
+ | * No recording available (State of the Institute - Mukherjee) | ||
=== <u>Week 5</u> === | === <u>Week 5</u> === | ||
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* | * | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *No recording available (Natural Language Processing I & II - Singh) |
==== Day 22: Optimization I and II, July 16 ==== | ==== Day 22: Optimization I and II, July 16 ==== | ||
*[[Media:bdsi_optimization_2019.pdf|Optimization slides]] - Kang | *[[Media:bdsi_optimization_2019.pdf|Optimization slides]] - Kang | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | * No recording available (Optimization I & II - Kang) |
==== Day 23: Writing from Point A to Point B and Bayesian Data Integration and Precision Medicine, July 17 ==== | ==== Day 23: Writing from Point A to Point B and Bayesian Data Integration and Precision Medicine, July 17 ==== | ||
*[[Media:Writing Clearly--Point A to Point B-2019.pptx|Writing from Point A to Point B slides]] - Griffiths | *[[Media:Writing Clearly--Point A to Point B-2019.pptx|Writing from Point A to Point B slides]] - Griffiths | ||
*[[Media:science-of-writing.pdf|Science of Writing paper]] - Griffiths | *[[Media:science-of-writing.pdf|Science of Writing paper]] - Griffiths | ||
+ | =====Recorded Lectures===== | ||
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=06dc5e25-839e-4ce9-98ab-aa8d00f14531 Data Integration & Precision Medicine] - Baladandayuthapani | ||
+ | * No recording available (Writing from Point A to Point D: Simple Strategies for Conveying Complex Ideas - Griffiths) | ||
==== Day 24: Radiation Oncology and Imaging Analysis and Optimization in Health, July 18 ==== | ==== Day 24: Radiation Oncology and Imaging Analysis and Optimization in Health, July 18 ==== | ||
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*[[Media:Zhang-2012b.pdf|Optimization of Prostate Biopsy Referral Decisions paper]] | *[[Media:Zhang-2012b.pdf|Optimization of Prostate Biopsy Referral Decisions paper]] | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8f823802-79bb-4893-856f-aa8e00f07b36 Cancer Surveillance] - Denton |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=6fe1b436-61cd-4679-93f1-aa8e00d33e09 Radiation oncology & precision medicine] - Rao | ||
==== Day 25: Confessions of a Clinical Researcher, July 19 ==== | ==== Day 25: Confessions of a Clinical Researcher, July 19 ==== | ||
* | * | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | * No recording available ( Better, Not Just Bigger Data Analytics: Confessions of a Clinical Researcher - Nallamothu) |
+ | * No recording available (Journey Lecture - Orozco del Pino) | ||
+ | * No recording available (Journey Lecture - Beesley) | ||
+ | * No recording available (State of the Institute - Zoellner) | ||
=== <u>Week 6</u> === | === <u>Week 6</u> === | ||
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*[[Media:WORD TRICKS AND TIPS.pdf|Word Tricks handout]] | *[[Media:WORD TRICKS AND TIPS.pdf|Word Tricks handout]] | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=7a959293-7303-4636-a1ad-aa9500e2a612 CVs & Resumes] - Forbes |
+ | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=3fecb1a7-af27-4b87-8e6e-aa9500e2afcf Preparing for Grad School] - Kidwell | ||
==== Day 27: Pick Me!, July 23 ==== | ==== Day 27: Pick Me!, July 23 ==== | ||
* | * | ||
=====Recorded Lectures===== | =====Recorded Lectures===== | ||
− | * | + | * No recording available (TBD - Grifftihs) |
== Day 29: Symposium == | == Day 29: Symposium == | ||
Line 257: | Line 301: | ||
* | * | ||
'''2019 Student Poster Presentations''' | '''2019 Student Poster Presentations''' | ||
− | * | + | *[https://umich.app.box.com/s/xwc8ecl2l3gahlpdhobkm0zbx4dvu3qa/file/496616682213 Data Mining Presentation] |
+ | *[https://umich.app.box.com/s/xwc8ecl2l3gahlpdhobkm0zbx4dvu3qa/file/496590467731 Machine Learning Presentation] | ||
+ | *[https://umich.app.box.com/s/xwc8ecl2l3gahlpdhobkm0zbx4dvu3qa/file/496560211380 Genomics Presentation] | ||
'''2018 Student Poster Presentations''' | '''2018 Student Poster Presentations''' | ||
*[https://drive.google.com/file/d/1TGNqkCAV9eBJ_-zHbiU-yo3N4Aowm_HB/view?usp=sharing Imaging Group Presentation] | *[https://drive.google.com/file/d/1TGNqkCAV9eBJ_-zHbiU-yo3N4Aowm_HB/view?usp=sharing Imaging Group Presentation] |
Latest revision as of 12:13, 6 June 2021
Welcome to the U-M Big Data Summer Institute 2019 Wiki!
Contents
- 1 Reading Material
- 2 2019 Presentations
- 2.1 Week 1
- 2.1.1 Day 1: RCRS Training, June 17
- 2.1.2 Day 2: Reproducible Research, Study Design and Inference, and Linear Regression, June 18
- 2.1.3 Day 3: Logistic Regression, Observational Data and Bias, and Probability, June 19
- 2.1.4 Day 4: Causal inference, Parameter Estimation/Likelihood, and Linear Algebra, June 20
- 2.1.5 Day 5: Data Wrangling in R with dplyr, Parts I and II, June 21
- 2.2 Week 2
- 2.2.1 Day 6: Visualization Data in R with ggplot2 - Part I & II and Generalized Linear Models, June 24
- 2.2.2 Day 7: Machine Learning I & Model Selection, June 25
- 2.2.3 Day 8: Machine Learning II & Unsupervised Learning/Clustering I, June 26
- 2.2.4 Day 9: Unsupervised Learning/Clustering II and Model Selection II, June 27
- 2.2.5 Day 10: Python Workshop I and II, June 28
- 2.3 Week 3
- 2.4 Week 4
- 2.4.1 Day 16: From Genomics to Prevention of Cardiovascular Diseases and R Markdown, July 8
- 2.4.2 Day 17: Bayes Computation I and II, July 9
- 2.4.3 Day 18: Reading Like a Scientific Writer and Social Network, July 10
- 2.4.4 Day 19: Stroke Disparities and Human-Centered Computing: Using Speech to Understand Behavior, July 11
- 2.4.5 Day 20: Spatial Epidemiology, July 12
- 2.5 Week 5
- 2.5.1 Day 21: Natural Language Processing I and II, July 15
- 2.5.2 Day 22: Optimization I and II, July 16
- 2.5.3 Day 23: Writing from Point A to Point B and Bayesian Data Integration and Precision Medicine, July 17
- 2.5.4 Day 24: Radiation Oncology and Imaging Analysis and Optimization in Health, July 18
- 2.5.5 Day 25: Confessions of a Clinical Researcher, July 19
- 2.6 Week 6
- 2.1 Week 1
- 3 Day 29: Symposium
- 4 Additional Resources
Reading Material
Machine Learning Group
Research Lecture Slides
- Introduction
- Explore MIMIC
- Getting x and y
- Some tips
- Sample Pipeline
- Training Pipleline
- CNN
- LSTM
- Structuring
- Dataset and DataLoader
- pytorch models
- Model Development
- Population
- Benchmark Features
- Inclusion Exclusion
Readings
- ARF Epidemiology
- CNN for Sentence Clarification
- Learning from Heterogenous Temporal Data
- MIMC 3
- MIMIC Benchmarks and Multitask RNN
- RNNs for Multivariate Time Series
- TREWScore for Septic Shock
- TREWScore Supplement
Genomics Group
Lectures
Intro Exercises
Papers
Population Genetics
Single Cell RNA
Transcriptomics
Online videos to better understand genetics and genomics
Genetics
- Introduction to Genetics by 23andMe (5 videos)
- TED-Ed : How Mendel's pea plants helped us understand genetics - Hortensia Jiménez Díaz
- Genetic Recombination and Gene Mapping by Bozeman Science
- Useful Genetics : A college-level comprehensive genetics course with 292 lectures offered by Rosie Redfield at UBC
Useful 3D Animations
- From DNA to protein - 3D Animation
- DNA Transcription - 3D Animation
- DNA splicing - 3D Animation
- mRNA Translation - 3D Animation
- How DNA is packaged - 3D Animation
- The Central Dogma - 3D Animation
Gene Regulation and Epigenetics
- Epigenetics Lecture by SciShow
- Hi-C Technique : A 3D map of the Human Genome
- The ENCODE Project
- RNAi by Nature Video
Sequencing Technologies
- TED-Ed : The race to sequence the human genome - Tien Nguyen
- DropSeq - Droplet-based Single Cell Sequencing by McCarroll Lab
Data Mining on Large Complex Datasets
Papers
2019 Presentations
Week 1
Day 1: RCRS Training, June 17
- Al-Marzouki - The effect of scientific misconduct on the results of clinical trials: A Delphi survey
- Baggerly Coombes - Deriving Chemosensitivity from cell lines: forensic bioinformatics and reproducible research in high-throughput biology
- Benjamini - Redefine statistical significance
- Ethical guidelines - Ethical Guidelines for Statistical Practice article
- Ethics reviews - Ethical statistical practice review slides
- Moving to a World beyond - Moving to a World Beyond “p < 0.05”
- On being a scientist - On being a scientist article
- On being a scientist ppt - On being a scientist slides
Recorded Lectures
- Cluster computing - Dan Barker
- RCRS Training - Mukherjee
Day 2: Reproducible Research, Study Design and Inference, and Linear Regression, June 18
- Reproducible Research LeFaive
- Study design and Inference Little
- Linear regression Hector
Recorded Lectures
- Reproducible research - LeFaive
- Study designs & Inference - Little
- Linear regression - Hector
Day 3: Logistic Regression, Observational Data and Bias, and Probability, June 19
- Logistic regression - Hector
- Observational data and Bias - Little
- Probability - Hartman
Recorded Lectures
- Logistic regression - Hector
- Observational Data, Bias - Little
- Probability review - Hartman
Day 4: Causal inference, Parameter Estimation/Likelihood, and Linear Algebra, June 20
- Causal Inference - Wu
- Parameter estimation and Likelihood - Little
- Linear algebra - Hartman
Recorded Lectures
- Causal Inference - Wu
- Parameter Estimation / Likelihood - Little
- Linear Algebra - Hartman
Day 5: Data Wrangling in R with dplyr, Parts I and II, June 21
- Dplyr slides - Flickinger
- Dplyr flight practice - Flickinger
- Dplyr flight practice answers - Flickinger
- Dplyr and OCLS practice - Flickinger
- Dplyr and OCLS practice answers - Flickinger
- Dplyr code - Flickinger
- Journey lectures - Boehnke
Recorded Lectures
- R Workshop dplyr Part II - Flickinger
- Journey Lecture - Boehnke
- No Recording Available (Data Wrangling in R with dplyr - Flickinger)
Week 2
Day 6: Visualization Data in R with ggplot2 - Part I & II and Generalized Linear Models, June 24
- Ggplot2 slides - Flickinger
- Ggplot2 mpg exercise - Flickinger
- Ggplot2 mpg excercise answers - Flickinger
- Ggplot2 flights exercise - Flickinger
- Ggplot2 flights answers exercise - Flickinger
Recorded Lectures
- Visualizing Data in R Part I - Flickinger
- Visualizing Data in R - Part II - Flickinger
- Generalized Linear Models - Hartman
Day 7: Machine Learning I & Model Selection, June 25
- Model selection I & II slides - Beesley
- Machine Learning I slides - Wiens
Recorded Lectures
- Model Selection 1 - Beesley
- No recording available (Machine Learning I - Wiens)
Day 8: Machine Learning II & Unsupervised Learning/Clustering I, June 26
- Machine Learning II slides - Wiens
Recorded Lectures
- Correlated data models - Hartman
- No recording available (Machine Learning II - Wiens)
- No recording available (Unsupervised Learning, Clustering I - Koutra)
Day 9: Unsupervised Learning/Clustering II and Model Selection II, June 27
- Model Selection II slides - Beesley
Recorded Lectures
- Model Selection Part II - Beesley
- Assessment of predictive models - Boonstra
- No recording available (Unsupervised Learning, Clustering II - Koutra)
Day 10: Python Workshop I and II, June 28
- Python Workshop I and II - Kamran
Recorded Lectures
- Python Workshop - Kamran
- Python workshop Part II - Kamran
- Journey Lecture - Banerjee
Week 3
Day 11: Data Mining I and Visualization I, July 1
- Visualization I slides - Kay
Recorded Lectures
- Data Mining Part I - Gryak
- Visualization I - Kay
Day 12: Data Mining II and Precision Health, July 2
- Precision Health slides - Kheterpal
Recorded Lectures
- Precision Health - Kheterpal
- No recording available (Data Mining II - Gryak)
Day 13: Visualization II and Intro to Bayes I, July 3
- Visualization II slides - Kay
- Intro to Bayes I slides - Wen
Recorded Lectures
- Introduction to Bayes - Wen
- No recording available (Visualization II - Kay)
Day 14: July 4 - NO CLASS
Day 15: Intro to Bayes II, July 5
- Intro to Bayes II slides - Wen
Recorded Lectures
- Journey lecture - Panigrahi
- Introduction to Bayes II - Wen
- No recording available (Journey Lectures: Taylor)
- No recording available (State of the Institute: Mukherjee)
Week 4
Day 16: From Genomics to Prevention of Cardiovascular Diseases and R Markdown, July 8
Recorded Lectures
- Genomics to Prevention of Cardiovascular Disease - Surakka
- R Markdown - Boonstra
Day 17: Bayes Computation I and II, July 9
Recorded Lectures
- No recordings available (Computation I & II - Chen)
Day 18: Reading Like a Scientific Writer and Social Network, July 10
- Reading Like a Scientific Writer slides - Griffiths
Recorded Lectures
- No recording available (Reading like a scientific writer - Griffiths)
- No recording available (Social Network - Adar)
- No recording available (Journey Lecture-Bowman)
Day 19: Stroke Disparities and Human-Centered Computing: Using Speech to Understand Behavior, July 11
- Stroke Disparities slides - Lisabeth
- Human-Centered Computing slides - Provost
Recorded Lectures
- Stroke disparities - Lisabeth
- No recording available (Human-Centered Computing: Using Speech to Understand Behavior - Provost)
Day 20: Spatial Epidemiology, July 12
- Spatial Epidemiology slides - Zelner
Recorded Lectures
- Journey Lecture - Spino
- No recording available (Spatial Epidemiology - Zelner)
- No recording available (State of the Institute - Mukherjee)
Week 5
Day 21: Natural Language Processing I and II, July 15
Recorded Lectures
- No recording available (Natural Language Processing I & II - Singh)
Day 22: Optimization I and II, July 16
- Optimization slides - Kang
Recorded Lectures
- No recording available (Optimization I & II - Kang)
Day 23: Writing from Point A to Point B and Bayesian Data Integration and Precision Medicine, July 17
- Writing from Point A to Point B slides - Griffiths
- Science of Writing paper - Griffiths
Recorded Lectures
- Data Integration & Precision Medicine - Baladandayuthapani
- No recording available (Writing from Point A to Point D: Simple Strategies for Conveying Complex Ideas - Griffiths)
Day 24: Radiation Oncology and Imaging Analysis and Optimization in Health, July 18
- Radiation Oncology slides - Rao
- Optimization in Health slides - Denton
- Two Stage Biomarker Protocols paper
- Optimizing Active Surveillance Strategies paper
- Optimization of Prostate Biopsy Referral Decisions paper
Recorded Lectures
- Cancer Surveillance - Denton
- Radiation oncology & precision medicine - Rao
Day 25: Confessions of a Clinical Researcher, July 19
Recorded Lectures
- No recording available ( Better, Not Just Bigger Data Analytics: Confessions of a Clinical Researcher - Nallamothu)
- No recording available (Journey Lecture - Orozco del Pino)
- No recording available (Journey Lecture - Beesley)
- No recording available (State of the Institute - Zoellner)
Week 6
Day 26: Preparing for Graduate School and CVs and Resumes, July 22
- Preparing for Graduate School slides - Kidwell
- CVs and Resumes slides - Forbes
- Resume Rubric slides
- CV Guide handout
- Action Verb handout
- Resume Samples handout
- Word Tricks handout
Recorded Lectures
- CVs & Resumes - Forbes
- Preparing for Grad School - Kidwell
Day 27: Pick Me!, July 23
Recorded Lectures
- No recording available (TBD - Grifftihs)
Day 29: Symposium
2019 Professor Lectures Presentations
2019 Student Poster Presentations
2018 Student Poster Presentations
- Imaging Group Presentation
- Machine Learning Group Presentation
- Genetics Group Presentation
- Data Mining Presentation
2017 Student Poster Presentations
2017 Symposium Reference Files
2017 Symposium Projects
- A Time-to-Event Analysis of Heart Failure via Electronic Health Records
- Melanoma Detection by Classifying Skin Lesion Images
- Classifying Skin Lesions Images Using Adaptive Boosting
- Machine Learning Classification of Skin Lesion Images
- Genomics: Genome Storage and Assembly
- Predicting the Transcriptome from the Genome
- Classification of Cell Types from Peripheral Mononuclear Blood Cells
- EHR-Based Study of Long-Term Infectious Diseases
- Visualizing Lab and Phenotype Associations Using PheWAS and Electronic Health Records
- Data Mining: Microenvironment Microarray Spot Based Approach for Cell Prediction
- Estimating Cell Growth with Machine Learning and Data Mining
Additional Resources
- Daily Schedule - Last update June 4, 2019
- Social events Schedule - Last update June 6, 2019