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Welcome to the U-M Big Data Summer Institute 2019 Wiki!

Contents

Reading Material

Machine Learning Group

Research Lecture Slides

Readings

Genomics Group

Lectures
Intro Exercises
Papers
Population Genetics
Single Cell RNA
Transcriptomics

Online videos to better understand genetics and genomics

Genetics
Useful 3D Animations
Gene Regulation and Epigenetics
Sequencing Technologies

Data Mining on Large Complex Datasets

Papers

2019 Presentations

Week 1

Day 1: RCRS Training, June 17

Recorded Lectures

Day 2: Reproducible Research, Study Design and Inference, and Linear Regression, June 18

Recorded Lectures

Day 3: Logistic Regression, Observational Data and Bias, and Probability, June 19

Recorded Lectures

Day 4: Causal inference, Parameter Estimation/Likelihood, and Linear Algebra, June 20

Recorded Lectures

Day 5: Data Wrangling in R with dplyr, Parts I and II, June 21

Recorded Lectures

Week 2

Day 6: Visualization Data in R with ggplot2 - Part I & II and Generalized Linear Models, June 24

Recorded Lectures

Day 7: Machine Learning I & Model Selection, June 25

Recorded Lectures

Day 8: Machine Learning II & Unsupervised Learning/Clustering I, June 26

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

Recorded Lectures

Day 10: Python Workshop I and II, June 28

Recorded Lectures

Week 3

Day 11: Data Mining I and Visualization I, July 1

Recorded Lectures

Day 12: Data Mining II and Precision Health, July 2

Recorded Lectures

Day 13: Visualization II and Intro to Bayes I, July 3

Recorded Lectures

Day 14: July 4 - NO CLASS

Day 15: Intro to Bayes II, July 5

Recorded Lectures

Week 4

Day 16: From Genomics to Prevention of Cardiovascular Diseases and R Markdown, July 8

Recorded Lectures

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

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

Recorded Lectures
  • Stroke disparities - Lisabeth
  • No recording available (Human-Centered Computing: Using Speech to Understand Behavior - Provost)

Day 20: Spatial Epidemiology, July 12

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

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

Recorded Lectures

Day 24: Radiation Oncology and Imaging Analysis and Optimization in Health, July 18

Recorded Lectures

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

Recorded Lectures

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

2017 Student Poster Presentations

2017 Symposium Reference Files
2017 Symposium Projects

Additional Resources