Learning outcomes
By the end of the course participants will know relevant databases for biological data (incl. genomic regions, protein domains, protein-protein interactions, gene expression data, Gene Ontology). The course will give an overview of the main bioinformatics methods that the attendee can later use in his/her research projects that involve the analysis of genetic information and/or design of novel genetic circuits. The course offers an alternative to the classical form of bioinformatics courses in terms of additional modules focused on genome engineering and rational design of chromosomes. It also introduces an innovative Synthetic Biology Open Language (SBOL): a community standard for communicating designs in synthetic biology.
Participants of the course will receive the following set of skills:
1) In silico analysis of cellular processes: genetic information and its manifestations.
2) Ability to apply bioinformatics methods for analysing gene regulation (incl. sequence alignment and analysis, primer design, gene expression analysis, CRISPR).
3) Will know relevant databases for biological data (incl. genomic regions, protein domains, protein-protein interactions, gene expression data, Gene Ontology).
4) Basic skills in in silico assembly of synthetic organisms in the Synthetic Biology Open Language (SBOL)- from hereditary material to metabolic pathways.
Brief description of content
The course consists of three modules:
I - Introductory bioinformatics module
* In silico analysis of single genes and proteins - basic search algorithms (blast), retrieval options, file types, alignment options, phylogenetic tree building etc.
* Design of primers for single genes - PCR primers, cDNA cloning primers
* Analysis of genomic regions - enhancers, promoters, coding regions, intron-exon. structure, (alternative) splicing, overlapping genes (including miRNA genes)
* Analysis of gene expression data (RNA seq, microarray, protein arrays, chip data).
* Analysis of interactome and GO data.
* Analysis of protein interaction networks.
