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 2014–2016
Curricula Guide is archieved. Please refer to current Curricula Guides
BIOI4211 Genomics, Transcriptomics and Proteomics 5 ECTS
Organised by
Bioinformatics
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

After completing this course the student can: find and use major Internet sources for genome-wide data; describe how modern high-throughput methods generate sequence data, gene expression data, genome methylation data, and protein binding data in the genome DNA; use genome browsers to access and retrieve data of genome, transcript and protein sequences, gene regulation, genome variations and genome comparisons; describe methodology and pipelines used in gene prediction and genome annotation; perform individual gene predictions; describe basic workflows of microarray data analysis and next-generation sequencing data analysis; describe the goals and experimental methods in proteomics and metabolomics; identify proteins by mass spectroscopic data using web-based tools.

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

Lectures and Moodle activity and assignments and written exam.

Teaching language

English

Modes of study

Learning diary, exam

Evaluation and evaluation criteria

Numeric 0-5.
Your learning will be evaluated based on your Moodle activity (2/3 weight) and the final exam (1/3 weight). Evaluation criteria include demonstrating the understanding of key concepts in your Moodle postings, and reflection of your learning. Your postings can be 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

Recommended year of study

1. year spring

Study materials

As presented in the course Moodle site. Including external web pages and original articles.

Belongs to following study modules

Department of Future Technologies
Department of Future Technologies
Department of Biochemistry
Department of Biochemistry
2014–2015
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Implementation details are unavailable.
Department of Future Technologies
DP in Computer Science
DP in Computer Science
DP Bachelor of Science in Techn.(Communication St)
DP in Information and Communication Technology
Finnish Study Modules