Data Visualization and Machine Learning — Using Python Modules to Solve Phylogenetics in Cancer Evolution

Abstract

The genome in every cell contains enormous information on how the cell would behalf. The difference between each genome results in various phenotypes. In this talk, I would first showcase how did we use python modules to extract information across different single-cell genome sequencing information from sparse and erroneous raw data. Secondly, I would demo example graphs where Python module seaborn and matplotlib aid creating novel and informative representation.

Speaker

Liting Chen

Liting is a PhD student in the Netherlands. She has currently started to work on the application of machine learning algorithms to understanding diseases. Other than research, she enjoys nature, music, and sharing ideas with people.