This course facilitates the conceptual transition from individual genes and proteins to full datasets of genomes, transcriptomes and proteomes. In addition, you learn how to utilize large datasets for extracting information of individual genes and proteins.
Learning outcomes
Familiarity with Internet sources for genome-wide data; basic skills in using tools at these web sites; understanding how modern high-throughput methods generate sequence data and gene and protein expression data; practical skill of using genome browsers to access genome data and genome comparison data; understanding gene prediction and genome annotation pipelines; skill of perfoming individual gene predictions; understanding different levels of variation in human genomes; understanding basic workflows of microarray data analysis and next-generation sequencing data analysis; basic knowledge of experimental methods in proteomics and metabolomics which enables understanding data analysis in these fields; skill of identifying proteins from mass spectroscopic data.
Contents
Next-generation sequencing (NGS); Ensembl genome browser and its comparative genomics tools; gene variations and variation databases; metagenomics; transcript expression data from microarrays and NGS, and principles of their analysis; finding over- and under-expressed genes from expression data; clustering of data; concept of functional enrichment; proteomics of protein expression, interactions and structures; and metabolic networks and metabolomics data.
Teaching methods
Teaching method
Contact
Online
Independent work
0 h
80 h
The course can be started at any time, with a deadline of 12 weeks after starting.
Teaching language
English
Modes of study
In addition to your reflection and summaries, the learning diary will contain exercises and assignments, which will be chosen individually, to be discussed with your tutor. Your learning diary can be written in Finnish if agreed with the web tutor.
Evaluation
and evaluation criteria
Numeric 1-5.
Your learning will be evaluated separately for the the sections of genomics, transcriptomics and proteomics, based on your learning diary work. Evaluation criteria include demonstrating the understanding of key concepts in your diary text, completing exercises successfully, working in the given 12-week deadline.
Recommended year of study
1. year autumn
1. year spring
First year in MSc or third year in BSc.
Study materials
Internet materials: Course pages and external web sites; original articles.