Module 1: Introduction to Bioinformatics
This module provides basic knowledge of how molecular data connects to modern biomedicine in order to give an understanding of background of genomic/personalized medicine. The course introduces the student to genomic data, DNA and protein sequence data and protein structures, major biological databases and teaches basic methods for their analyses.
Module 2: Computational Statistics for clinical doctors
This module will provide a practical introduction to analysis of biological and biomedical Big data, in order to develop a critical understanding of the reliability of analysis results. Clinical doctors will learn to appreciate how the R statistical environment can be applied to biological data analysis in a cost-efficient manner.
Module 3: Commercial personalised genomics services in patient care
The purpose of this module is to provide medical doctors the necessary knowledge and skills to interpret results from commercial personalized genomics services, like 23andMe, deCODE, Gene by Gene, etc. This module facilitates integrating these services into their patient care activities.
Module 4: Quality Improvement in Healthcare
This module programme will aim to equip trainees with a range of knowledge and skills, which are relevant and applicable in communications within healthcare contexts. Participants will learn how to build high-performing and engaged healthcare teams, establish and sustain effective clinical relationships, as well as implement strategies and tools to support patient-centered care. Additionally, with patient safety initiatives at the forefront of care, a major goal of this module will be to help health care professionals to develop the background knowledge and skills necessary for the specialty of risk management. This module is focused especially to the communication, ethics and risks associated with genetic testing and disease risk assessment.