Bioinformatics (BIO510)

This course provides a comprehensive overview of applied bioinformatics and programming, encompassing various key topics. These include access to bioinformatic databases; data analysis with help of sequence alignments and phylogenetic analysis; primer design for PCR, metabolomics data analysis. Furthermore, students will learn using Python programming for bioinformaitcs. Machine learning and AI are included in the course.


Course description for study year 2025-2026. Please note that changes may occur.

Facts

Course code

BIO510

Version

1

Credits (ECTS)

10

Semester tution start

Spring

Number of semesters

1

Exam semester

Spring

Language of instruction

English

Offered by
Time table

View course schedule

Content

NB! This is an elective course and may be cancelled if fewer than 10 students are enrolled by January 20th for the spring semester.

The course covers the following subjects in applied bioinformatics: gene/protein/metabolite databases, local and global multiple sequence alignments, construction of phylogenetic trees, sequence analysis tools, primer construction for PCR/RT-PCR (QPCR), metabolomics data analysis, basic use of FTP, HTTP protocols, and introduction to Python programming for bioinformatics. Data analysis, simulations, visualization techniques, and artificial intelligence (AI) applications are included.

Learning outcome

Learning objectives:

  • To get a good overview of important bioinformatics tools (sequence alignments, construction of phylogenetic trees, sequence analysis tools, metabolomics data analysis)
  • To be able to use major bioinformatics software and databases
  • To learn primer construction for PCR
  • To learn basic programming for bioinformatic purposes.
  • To get an introduction to machine learning
  • To learn about Artificial intelligence (AI) applications.

Required prerequisite knowledge

None

Recommended prerequisites

BIO100 Cell Biology, BIO200 Biochemistry
Basic knowedge in molecular biology and biochemistry and computational skills are beneficial for completion of this course.

Exam

Form of assessment Weight Duration Marks Aid
Written assignment (Home exam) 1/1 2 Weeks Letter grades

Individual assignment. No resit options are offered on the assignment. Students who do not pass can retake this the next time the course is offered.

Coursework requirements

Compulsory exercises

The course includes the following compulsory elements:

  • Two compulsory submissions and a group assignment. Approved assignments are required to qualify for the final assignment.
  • 80% attendance at scheduled teaching hours is required to qualify for the final assignment.

Course teacher(s)

Course coordinator:

Daniela Maria Pampanin

Course teacher:

Klevia Dishnica

Head of Department:

Päivi Annele Teivainen-Lædre

Study Program Director:

Mark van der Giezen

Coordinator laboratory exercises:

Liv Margareth Aksland

Method of work

2 hours lectures and 2 hours practical computer exercises per week.

Overlapping courses

Course Reduction (SP)
Bioinformatics (MOT290_1) 10

Open for

If the number of participants needs to be limited, priority will be given to Master students in Biological Chemistry.

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Literature

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