【MIT-AI+医学课程】面向生命科学的深度学习课程

本课程更广泛地介绍了基因组学和生命科学的基础和最先进的机器学习挑战。我们介绍了深度学习和经典机器学习方法来解决关键问题，比较和对比它们的力量和局限性。我们力求使学生能够评估我们在这个快速发展的领域所面临的关键问题的各种各样的解决方案，并执行能够产生巨大影响的新的使能解决方案。作为课程的一部分，学生将实施具有挑战性的问题的解决方案，首先是在一个精心选择的任务集的问题集，然后在一个独立的项目。学生将在Jupyter笔记本中使用Python 3和TensorFlow 2进行编程，这是对仔细记录你的工作的重要性的认可，这样别人就可以精确地复制你的工作。

https://mit6874.github.io/

week1: Course Intro, AI, ML week2: Machine Learning Foundations

week3: CNNs week4: RNNs、Transformers、GNN、LSTM

week5: Interpretable Deep learning

week6: Generative Models，GANs, VAEs，Learning Representations

week7: DNA Accessibility， Promoters and Enhancers week8: Transcription Factors, DNA methylation

week9: Gene Expression, Splicing

week10: Single cell RNA-sequencing

week11: Dimensionality Reduction, Genetics, and Variation week12: GWAS and Rase variants

week13: eQTLs

week14: Electronic health records and petient data

week15: Graph Neural Networks week16: AI for Drug Design

week17: Deep Learning for Protein folding

week18: Machine learning for Pathology

week19: Deep learning for Cell Imaging segmentation(可选) week20: Deep learning Image Registration and analysis（可选） week21: Electronic health records（可选） week22: Deep learning and Neuroscience（可选）