Single-cell RNA-seq is gaining more and more popularity in the life sciences, as it helps us characterize biological processes at the cellular level. Often the first step in single-cell analyses is
determining which cell (sub-)types are present in a sample and assigning each cell to a cell type
using expression of marker genes . In this project, you will employ machine learning methods to
build an automated cell type classifier by using publicly available reference datasets and evaluate their performance on available in-house datasets.
Study program(s)
Bioinformatics and Systems Biology
Biological Sciences
Biomedical Sciences
