This is the repository for the Applications of Machine Learning and Artificial Intelligence in Biomedical Informatics (BMI8050 on Autumn 2020), organized by Cankun Wang.
- Guest - Predictive modeling using R markdown.
- Chapter 1 - Introduction to Jupyter Notebooks: The entirety of every chapter of is available as an interactive Jupyter Notebook. Since the most important thing for learning deep learning is writing code and experimenting, it's important that you have a great platform for experimenting with code.
- Chapter 2 - Mechanisms of Action (MoA) Prediction using DNN models.
- Chapter 3 - DCNet - A simple LSTM-RNN for generating sequence consensus.
- Chapter 4 - A tutorial of DNA motif finding using CNN.
- Chapter 5 - A tutorial of predicting protein-protein interactions using GCN.
- Chapter 6 - A tutorial of dimension reduction in single-cell RNA-seq dataset using Autoencoder.
- Final - Final reports for each students
To download all course material, type the following into the command-line:
git clone git@github.com:OSU-BMBL/BMI8050-2020.git
Or simply download an archived course contents:
Launch Jupyter server on OSC:
To update the repository and keep the modified files:
git stash && git pull && git checkout stash -- .
Author: Cankun Wang
Repository material is inspired by the following courses:
- fastbook by fastai
- Neural Networks and Deep Learning by Andrew Ng