PVS0141, Introduction to bioinformatics, 10.0 Hp
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Syllabus

Level

Third cycle

Subject

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

After completion of the course, the student should be able to:

• understand and describe the basic principles of bioinformatics
• independently carry out comparisons of protein and DNA sequences, and to interpret the results
• work within Unix/Linux operating systems
• build a bioinformatics "workbench" with publicly-available programs that are suited to his/her own needs
• use biological databases
• describe the statistical methods on which bioinformatics is based
• perform bioinformatics analysis and critically evaluate, validate and judge the results

Content

The course aims to give the student a solid foundation in the basic methods of bioinformatics. It will cover the theories, algorithms and practical applications of computer-based methods for analysis of DNA sequences and protein structures. The topics to be covered include:

• biological databases
• homology analysis
• sequence analysis (with emphasis on the package EMBOSS and UGENE)
• statistics and R introduction
• web-based tools for analysis
• the Unix operating system
• phylogeny
• comparative genomics
• functional genomics
• Next Generation Sequencing (NGS)

The course is mainly based on lectures, interactive computer exercises and web-based tutorials.

Examination Formats and Requirements for Passing the Course

Written exam and web-based tasks.

Responsible Department/Equivalent

Department of Animal Breeding and Genetics

Supplementary information

Other Information

The participants must bring own computers. The course will take place in the SLU campus Ultuna in Uppsala. Course application: by e-mail to course coordinator. The course is given jointly with the advanced course SLU-30254 Bioinformatics 15.0 HEC, and is part of the GS-VMAS Research School at SLU.

For application: https://www.slu.se/gs-vmas-courses