Advanced Single-Cell Genomics (ASCG)

Since Robert Hooke’s discovery of cells in 1665, we accumulated more information about sub-cellular structures and cellular functions, and more evidence that the cell is the fundamental unit of life. Such a new understanding was the start of shaping one of the key ideas in biological history: The cell theory.

The discovery of cells changed our perspective on the underlying structure of tissues and organs. We started to understand that alterations in the cells of an organism would have a causal link to diseases, and we started to catalog human diseases accordingly. It seems that the interaction between the human mind, tools, and technologies induces the next steps in understanding the underlying chain of causes and effects of the physical world.

Now, we have new high-throughput technologies that enable us to unravel the underlying genetic and epigenetic regulation of biological systems, coupled with imaging and spatial information at the single-cell resolution. These technologies generate a huge amount of data, which gives us exciting challenges to develop computational and machine learning approaches for single-cell genomics data analysis and integration.

This course will be an exciting learning journey into the data science of single-cell genomics, which will help learners be part of this new and revolutionary understanding of biological systems in health and disease.

Lecture and Practicum Planning:
– 12 Weeks
– Language: English

Pre-requisites:
– Previous experience and knowledge about NGS data-analysis.
– Deep knowledge of a programming language (R or Python).
– Good understanding of machine-learning and statistical-inference models.

Course Objectives:
– Overview of the current technological advances in the single-cell genomics field.
– Deep theoretical understanding of the state-of-the-art computational methods and algorithms for analyzing single-cell genomics data.
– Hands-on and practical experience in analyzing and integrating single-cell genomics data.
– Developing practical skills and intuition for data interpretation across different biological contexts.

Assessment:
– Presenting recent original research papers and review articles.
– Mini-projects and tasks/assignments over the course weeks.
– Final Project Presentation.