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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

Lecture Notes

• Recurrent Neural Networks
• Convolutional Neural Networks
• Deep Learning
• BDSI Lecture
• Flux Guide
• Python Guide
• Python Tutorial

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

Day 29: Symposium

2019 Professor Lectures Presentations

2019 Student Poster Presentations

2018 Professor Lectures Presentations

• 2018 Symposium Flyer
• Symposium Welcome Remarks
• Calibration Concordance - Chen
• Data Science and Predictive Health Analytics - Dinov
• Models of Human Choice - Feinberg
• Linking Tumor with Personalized Medicine - Rao
• Humanist Approach to Data Science - Schutt
• Big Data in the Social Sciences - Titunik
• Detecting Epistasis in Large Scale Genetic Mapping - Zhou

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

• DataCamp Resources
• File:BDSI 2019 Master Schedule.docx - Last update July 3, 2018