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1
Introduction
2
Goals of the Course
3
Course at a Glance
4
Why Computational Biology
5
Why GenAI is different
6
Representation Learning: Images + Genomes
7
Graph Representation Learning in GNNs
8
Language Representation Learning in LLMs
9
Visualizing Z vector Embedding Landscapes
10
The Road Ahead
Description:
Explore the foundations of computational biology and machine learning in this introductory lecture. Delve into the course goals, structure, and significance of computational biology in modern research. Examine the unique aspects of generative AI and its applications. Investigate representation learning techniques for images and genomes, graph neural networks, and language models. Visualize embedding landscapes and gain insights into future developments in the field. Prepare for an in-depth journey through the intersection of biology and artificial intelligence.

Introduction to Machine Learning in Computational Biology - Lecture 1

Manolis Kellis
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