Content (Syllabus outline)
- overview of the bioinformatics landscape in medicine: technologies and applications
- overview of open-source bioinformatics software applications
- programming and database management for bioinformatics in medicine: Linux OS (commands, applications and scripting), RDBMS (MySQL)
- advanced data management and data management plans with data stewardship wizard
- advanced methods for medical omics data analysis in R
- medical data archives (National genome/phenome research data archive), databases and resources
- Open access and FAIR data principles
- health information systems and applications/clinical registries
- clinical data standards
- Clinical Decision Making and Care Process Improvement
- High Performance Computing
- machine learning
- big data
- semantic searches and natural language processing (NLP)
- concepts of genomics and techniques for genomic data acquisition in medicine
- genome assembly (gene prediction) and functional annotation techniques in medicine
- DNA sequencing analysis in medicine
- analysis of complex disease association studies
- concepts of transcriptomics and techniques for transcriptomic data acquisition in medicine
- analysis of microarray (gene expression, CNV, genotyping) data in medicine
- next generation sequencing (NGS) analysis in medicine
- single-cell analyses (scRNAseq, ATAC, spatial transcriptomics, …) in medicine
- concepts of epigenomics and techniques for epigenomic data acquisition in medicine
- establishing bioinformatics protocols/workflows and LIMS for single-cell analyses, NGS and 3rd generation sequencing (3GS) in medicine technologies
- personalized medicine
- ethics in medical omic analyses
Prerequisites
Prerequisites for admittance to final exam:
Practical examination (colloquium):
- presence at at least 80% of practicals,
- seminar presentation.
Exam:
- practical examination (colloquium),
- seminar presentation,
- project/paper presentation.