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Vår 2022

FSK-3053 Bioinformatics for aquatic biology and aquaculture - 10 stp


The course is administrated by

Faculty of Biosciences, Fisheries and Economics

Type of course

The course is available as a singular optional course within the program Fiskeri - og havbruksvitenskap and Biology programs.

Course contents

The objective of this course is to learn how bioinformatics tools can be used for problem solving in ecology of marine and freshwater environments, fisheries, and aquaculture. The course will provide training in the use of relevant bioinformatic concepts, software for bioinformatic analysis and programming languages (e.g. R). The students will be trained in the use of remote computing environments and online data resources. The course will focus on relevant ecological and industrial problems that can be solved with molecular genetics and bioinforElectmatics tools. We will cover methods for population genomics, transcriptomics, molecular biodiversity assessment, and species detection from environmental DNA.

Application deadline

Applicants from countries within EU/EEA: December 1st for the spring semester. Exchange students and Fulbright students: 1 October for the spring semester.

Admission requirements

Admission to FSK-3053 requires a Bachelor's degree (180 ECTS) in Fiskeri- og havbruksvitenskap or Biology. 

FSK-2053 Data science and bioinformatics for fisheries and aquaculture, or equivalent course in data science and bioinformatics, is a requirement.

Biological knowledge, e.g. from the FHV or biology programs, is an advantage. Previous experience in programming languages (e.g. R) and as an user of Linux systems is an advantage.

9371 - application code singular course.


Obligatory prerequisites

FSK-2053 Data science and bioinformatics for fisheries and aquaculture

Objective of the course

The students will obtain;

Knowledge

Skills

Competence


Language of instruction

The course will be taught in English. The students can choose the language they prefer for writing their exercises and home project (Norwegian or English).

Teaching methods

The teaching will be a combination of theoretical lectures and practical exercises, with seminars to discuss results of different approaches to relevant practical problems. An important part of the sessions will be taught in the computing classroom, so the students can have access to online resources and tools. 

Assessment

The exam consists of 2 parts:

The grading scale is A - F, where F is fail.

The students will get feedback on their part-exams and final home project, and they will be allowed to submit a revised version of the home exam to improve the final grade.

There will not be a re-sit examination for students that did not pass the previous ordinary examination. 

Lectures Spring 2022
Undervisning post.doc. Owen Simon Wangensteen Fuentes