BK0004, Bioinformatics, 15.0 Hp
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Syllabus

Finalized by: PN-VH, 2024-11-14
Valid from : Autumn semester 2025 (2025-09-01)

Level

Second cycle (A1N)

Main field of study

Bioinformatics

Grading Scale

The grade requirements within the course grading system are set out in specific criteria. These criteria must be available by the course start at the latest.

Course language

English

Entry Requirements

Objectives

The course aims to give a solid basis in basic bioinformatic methods. It covers the theories, algorithms and practical applications of computer-based methodology for the analysis of DNA/protein sequences, protein structures, and data produced by large-scale methods for understanding interactions of different biomolecules.

Upon successful completion of the course, students will be able to

• account for the fundamental concepts within bioinformatics
• independently carry out homology analyses of both protein - and DNA sequences and interpret the results
• use the most common commands in Unix/Linux,
• use the most common commands in R,
• independently build a "workbench" for bioinformatics with publically available softwares suited to the own needs,
• use biological databases
• describe technologies within High Troughput Sequencing (HTS or NGS) and methods for the analysis of expression data that have been retrieved with RNAseq technology,
• management and anlalysis of large scale data sets,
• manage the use of software solutions in computer clusters and cloud services.

Content

Subject-related content

The course covers bioinformatic methods such as theories, algorithms and practical applications in computer-based methodology for the analysis of DNA/protein sequences, protein structures, annotation of genomes, metagenomics. The course also covers theories for the analysis of RNAseq expression data and different analytical methods within High Troughput Sequencing (sometimes called NGS).

Topics to be covered includes: biological databases, biostatistics, homology analyses, gene analyses (emphasis on open source softwares), web-based analytical tools, Unix OS, R, comparative genomics, functional genomics, metagenomics, molecular evolution, RNAseq expression analysis, management of large amounts of data, principles for the use of computer clusters, and cloud services and annotation of new genomes.

Teaching formats

To further student learning and promote discussion, a variety of methods are used: lectures, exercises, project work and laboratory sessions.

The course focuses on the following generic competencies

Information competence, problem solving and scientific methods.

The following components are compulsory

Exercises and laboratory sessions.

Examination Formats and Requirements for Passing the Course

Passed written and oral examination. Approved participation in compulsory components.

Responsible Department/Equivalent

Department of Animal Biosciences

Supplementary information

Module set

Title	Credits	Code
Project	5.0	0001
Exam	10.0	0002

The Course Replaces

BK0001