Uusi opinto-opas (sisältäen myös opetusohjelmat) lukuvuodelle 2018-2019 sijaitsee osoitteessa https://opas.peppi.utu.fi . Tältä sivustolta löytyvät enää vanhat opinto-oppaat ja opetusohjelmat.

The new study guide (incl. teaching schedules) for academic year 2018-2019 can be found at https://studyguide.utu.fi. This site contains only previous years' guides.

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Archived Curricula Guide 2013–2014
Curricula Guide is archieved. Please refer to current Curricula Guides
BIOI4211 Genomics, Transcriptomics and Proteomics 4 ECTS
Organised by
Bioinformatics
Person in charge
Martti Tolvanen
Planned organizing times
Period(s) I II III IV
2013–2014 X
Preceding studies
Compulsory:

General description

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

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Doctoral Students
  • Exchange Students
Study journal / learning diary
  • In English
English:
Study journal / learning diary and Agreement with teacher

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 0-5.
Your learning will be evaluated based on your learning diary work and Moodle activity. Evaluation criteria include demonstrating the understanding of key concepts in your diary text, completing exercises successfully, reflection of your learning, sharing of your ideas and findings in the forums, and working in the given 12-week deadline. Your learning diary is counted towards 80% of the total score. The diary will contain a mix of summaries, essays, discussion, and exercises/mini projects. For the highest grades, your diary should contain an element of reflectiveness (description of your learning process, what you consider to be the important things learned in each study session, questions you put to yourself); tackling many practical problems; and finding additional sources to support your learning. Your Moodle activity counts towards 20% of the total score. For "points" of Moodle activity, you can either start relevant discussions in the Moodle forums (for example, by sharing reports of analyses or mini projects you have completed), contribute meaningful comments/answers in a discussion, provide suggestions for new topics or resources for the course pages, or report new links to replace outdated ones.

Recommended year of study

1. year spring

Study materials

Internet materials: Course pages and external web sites; original articles.

Belongs to following study modules

Department of Future Technologies
Department of Future Technologies
Department of Future Technologies
2013–2014
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Implementation details are unavailable.
Department of Future Technologies
DP in Computer Science
DP in Electr. and Communication Technology
Finnish Study Modules