Teaching
Teaching at the University of Copenhagen
NBIK15013U – Genome Sequence Analysis
Introduction to next-generation sequencing technologies and computational analysis of sequencing data, from preprocessing of raw sequencing reads to downstream analyses, including RNA-seq, variant calling, single-cell sequencing, and statistical analyses using UNIX and R.
- For MSc students in Biology, Biochemistry, Biotechnology, Molecular Biomedicine, and Bioinformatics
- Credit: 7.5 ECTS
- Block: 2
NBIB25001U – Genomics & Transcriptomics
Introduction to next-generation sequencing technologies and computational analysis of sequencing data, from preprocessing of raw sequencing reads to downstream analyses, including RNA-seq, variant calling, single-cell sequencing, and statistical analyses using UNIX and R.
- For BSc students in Bioinformatics
- Credit: 7.5 ECTS
- Block: 2
NBIK20004U – Advanced Bioinformatics for Next-Generation Sequencing
Strategies for genomic variant interpretation, including expression quantitative trait locus (eQTL) analysis, statistical fine-mapping, functional annotation, and approaches for linking genetic variants to molecular function and disease.
- For MSc students in Bioinformatics
- Credit: 7.5 ECTS
- Block: 1
NBIK10005U, NBIK10008U, NBIK10009U, NBIK10010U – Bioinformatics Project
Individual research projects carried out under faculty supervision.
- For MSc students in Bioinformatics
- Credit: 7.5 ECTS
- Block: 1–4
Thesis projects
Interested in carrying out a Bioinformatics project or M.Sc. thesis in the Andersson Lab? Please send Robin an email to arrange a meeting and discuss possible projects.
Example project areas include:
- Machine learning models of gene regulation and regulatory DNA sequence
- Computational methods for identifying active regulatory elements from transcription initiation data
- Computational methods for mapping enhancer–gene interactions from single-cell genomics data
- Atlas-scale analysis of regulatory elements across cell types and biological systems
- Variant-to-function prediction and interpretation of noncoding genetic variation
Students are encouraged to develop independent research projects while working closely with members of the lab. Projects typically combine method development with applications to large-scale genomics datasets.