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

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

• BDSI Genomics Intro
• PopGen Intro

Intro Exercises

• Single Cell Exercise
• Single Cell R Code
• Intro Integrative

Papers

Population Genetics

• 1000 Genomes Project
• Cavalli SforzaHGDP 2005
• LiHGDP 2008
• NovembreNature 2008

Single Cell RNA

• Macosko_MouseRetinaDropSeq
• Single cell makes big data

Transcriptomics

• GamazonPrediXCan 2015
• GusevTWAS 2006

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

2019 Presentations

Week 1

Day 1: 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

Day 2: June 18

• Reproducible Research LeFaive
• Study design and Inference Little
• Linear regression Hector

Day 3: June 19

• Logistic regression - Hector
• Observational data and Bias - Little
• Probability - Hartman

Day 4: June 20

• Causal Inference - Wu
• Parameter estimation and Likelihood - Little
• Linear algebra - Hartman

Day 5: 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

Week 2

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

• Ggplot2 slides - Flickinger
• Ggplot2 mpg exercise - Flickinger
• Ggplot2 mpg excercise answers - Flickinger
• Ggplot2 flights exercise - Flickinger
• Ggplot2 flights answers exercise - Flickinger

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

• Model selection I & II slides - Beesley
• Machine Learning I slides - Wiens

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

• Machine Learning II slides - Wiens

Day 10: Python Workshop I and II, June 28

• Python Workshop I and II - Kamran

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

• Data Mining/ Machine Learning
• Electronic Health Records (EHR)
• Genomics
• Imaging

2017 Symposium Reference Files

• 2017 Symposium Program
• 2017 Symposium Flyer

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