Introduction to Omics

Undergraduate course

Course description

Objectives and Content

The course gives an introduction to bioinformatics related to processing and analysis of data produced using high-throughput omics technologies including next generation sequencing and mass spectrometry based proteomics. The course includes an introduction to relevant data generating technologies, the types of data produced, and processing steps utilized to prepare the data for analysis. Furthermore, the course includes methods for mapping reads to reference assemblies, for de novo assembly of genomes and transcriptomes, for analysis of alternative splicing, genomic variants, and for expression level estimation. In addition, the course covers approaches for detection of differential expression at the level of individual genes / proteins as well as of pathways / systems, through for example over-representation analysis.

Learning Outcomes

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:



The student

  • has a general understanding of key technologies used to generate omics data
  • Understands and is able to implement methods for quality control, filtering and normalization of NGS and proteomics data
  • Understands and is able to explain methods for sequence mapping, and for de novo assembly of genomes and transcriptomes
  • Understands and is able to explain methods for protein identification and analysis of post-translational modifications
  • Understands and is able to implement and use methods for detection and annotation of genomic variants
  • Understands and is able to implement methods for analysis of differential expression and over representation analysis



The student is able to

  • apply state of the art tools to analyze real sequencing and proteomics data sets
  • take part in designing an omics based experiment to address a certain biological question - and take a lead role in analyzing resulting data



General competence

The student can

  • Take part in teams performing and analyzing omics experiments to help address a biological question



ECTS Credits


Level of Study


Semester of Instruction

Required Previous Knowledge
For incoming exchange students: At least 60 ECTS in Computer Science and at least 10 ECTS in mathematics.
Recommended Previous Knowledge


BINF100 or corresponding background in bioinformatics and molecular biology. Be able to implement basic algorithms in a programming language of your own choice. Recommended background: INF100 and INF102. A basic understanding of algorithms and efficiency, as well as statistics, is required.

Credit Reduction due to Course Overlap
INF285: 5 STP
Access to the Course
Access to the course requires admission to a programme of study at The Faculty of Mathematics and Natural Sciences.
Teaching and learning methods

Teaching in form of lectures and mandatory exercises

Lectures, 4 hours per week

Exercises, 2 hours per week

Compulsory Assignments and Attendance
Compulsory assignments are valid for 1 subsequent semesters
Forms of Assessment

The forms of assessment are:

  • Mandatory exercises, 50 % of total grade.
  • Written examination (3 hours), 50% of total grade.

All compulsory assignments must be approved before examination.

Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Assessment Semester
Examination both spring semester and autumn semester. In semesters without teaching the examination will be arranged at the beginning of the semester.
Reading List
The reading list will be available within July 1st for the autumn semester and December 1st for the spring semester.
Course Evaluation
The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department.
Examination Support Material
Non-programmable calculator, according to the faculty regulations
Programme Committee
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.
Course Coordinator
Course coordinator and administrative contact person can be found on Mitt UiB, or contact Student adviser
Course Administrator
The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.