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Study plan for MAMN-INFBI Bioinformatics, spring 2024

Name of qualification

Master of Science in Informatics - bioinformatics

ECTS Credits

Two years of full-time study, where the normal workload for a full-time student is 60 credits for one academic year.

Full-time/Part-time

Full-time

Language of Instruction

English

Semester

Autumn

Objectives and content

Objectives

After studying this programme, a candidate with a Master's degree in informatics specializing in bioinformatics, will have substantial knowledge and advanced skills in bioinformatics, systems biology, analysis of molecular biology data as well as substantial skills in related programming. Due to the interdisciplinary nature of bioinformatics, the students are also given an introductory overview of specialized areas such as biology and medicine. In their Master's programme, the students are given a thorough introduction to scientific working principles, e.g., taking state-of-the-art research into account and presenting their own work.

Content

Visualization is a field of increasing relevance in molecular life science and its applications for example within medicine and environmental science. Advanced algorithms and methods from machine learning and data analysis are used to process and analyze large complex data sets. Data may come from measurements such as sequencing of DNA or RNA or measurements of protein abundance and activity. Molecular biology data are typically analyzed together with more high-level information for example about disease, response to treatment, or other parameters. Within bioinformatics we develop and apply methods for processing analyzing and presenting molecular biology data. Examples of applications are within personalized medicine prediction of response to treatment, within ecology analysis of molecular data reflecting species abundance in an environmental sample.

Required Learning Outcomes

A candidate who has completed his or her qualification should have the following learning outcomes defined in terms of knowledge skills and general competence:

Knowledge

The candidate

  • Can explain the theoretical foundation for the basic bioinformatic methods and discuss and justify the use of particular methods for solving relevant problems.
  • Can explain and discuss theory and/or scientific articles in selected, advanced subjects in bioinformatics and closely related fields of study.
  • Can show that he/she has an advanced knowledge of informatics in general, and specialized knowledge about a limited area in bioinformatics, related to the Master¿s thesis.
  • Can demonstrate sufficient knowledge about a biological field of study (e.g. molecular biology) such he/she is able to work in interdisciplinary teams

Skills

The candidate

  • Can develop programs to execute bioinformatic analyses.
  • Can use key data bases, tools and programming libraries for bioinformatics.
  • Can plan and perform analyses of real or simulated molecular biological data and consider the results in light of the hypotheses that are being tested.
  • Can perform an independent, limited research project under supervision, but with a great degree of independence and his/her own initiative in accordance with research ethics and norms.
  • Can collect, analyze and apply state-of-the-art knowledge in the field.
  • Can analyze and critically examine scientific sources of information and use them to structure and formulate a line of reasoning and new ideas in bioinformatics.
  • Can analyze, interpret and discuss his/her own results in a professional and critical way, and in light of methods and theories in the field.

General competence

The candidate

  • Can generally analyze scientific problems and participate in discussions with different approaches and solutions.
  • Can make good written and oral presentations of scientific topics and research results.
  • Can communicate about professional problems, analyses and conclusions in bioinformatics, with both specialists and the general public.
  • Can reflect upon key, ethical and scientific problems in his/her own work and in that of others.
  • Can demonstrate an understanding of and respect for scientific values about openness, precision, reliability and the importance of differentiating between knowledge and opinions.

Admission Requirements

The master's programme builds on a bachelor's degree from the Department of Informatics, or a bachelor's degree and at least 80 ECTS of Mathematics and Informatics/Computer science.

Bachelor's degrees from UiB that qualify:

  • Bachelor's degree from Department of Informatics, UiB (BAMN-BINF, BAMN-DSIK, BAMN-DTEK, BAMN-DVIT, BATF-IMØ, BAMN-INF)
  • Bachelor's degree in Information and Communication Technology (IKT) with at least 15 ECTS (at least two courses for at least 7,5 ECTS each) of elective Mathematics
  • Bachelor's degree in Cognitive Science (BASV-KOGNI) with specialization in Informatics
  • Bachelor's degree in Artificial Intelligence (BASV-AIKI) qualifies, if you have at least 80 ECTS of Mathematics and Informatics/Computer Science. Out of these 80 ECTS, at least 40 ECTS must be in Informatics/Computer science, and at least 15 ECTS must be in Mathematics. One course in Statistics can count towards Mathematics (except STAT100). MNF130 and equivalent counts as Informatics. INF-courses and INFO-courses with credit reduction towards INF-courses count as informatics.

Bachelor's degrees that qualify

  • Bachelor's degree in Computing from HVL (Western Norway University of Applied Sciences)
  • Bachelor's degree in Information Technology from HVL
  • Bachelor's degree in Communication Systems from HVL

Other bachelor's degrees might qualify if you have at least 80 ECTS of Mathematics and Informatics/Computer Science. Out of these 80 ECTS, at least 40 ECTS must be in Informatics/Computer science, and at least 15 ECTS (at least two courses with 7,5 ECTS each) must be in Mathematics. If both INF100 and INF109 are part of the Bachelor's degree, the applicant will only get credits for INF100. One course in Statistics can count towards Mathematics (except STAT100). MNF130 (and equivalent) counts as Informatics.

For international self-financing applicants:

The Master's programme is not available for international applicants residing outside of the Nordic countries, the European Union/EEA and Switzerland.

You also need to document:

Recommended previous knowledge

It is strongly advised to take MOL100 Introduction to molecular biology. STAT200 Applied statistics is also recommended. Other courses can be chosen in agreement with supervisor.

Compulsory units

The master's programme consists of two components: Coursework of 60 credits and an individual research project (master's thesis) of 60 credits, a total 120 ECTS.

Advised study plan:

4. semester INF399 INF399 INF399

3. semester BINF305 INF399 INF399

2. semester BINF301/ Elective/STAT200 INF399

1. semester INF234 BINF201 Elective

Courses:

Four courses are compulsory:

INF234 Algorithms

BINF201 Introduction to omics

BINF301 Genome-scale algorithms

BINF305 Systems biology

In addition, there are 20 credits of elective courses, chosen in agreement with the supervisor.

We strongly advice to take MOL100 Introduction to molecular biology.

The other courses should be at 200- and 300-level. In agreement with the supervisor, it is possible to have 10 ECTS at 100-level. A suitable study plan should be planned together with a supervisor, so that a sufficient foundation is laid towards the Master thesis.

Master's thesis: INF399 Master's thesis in informatics of 60 credits (the student may, in consultation with the supervisor choose to write a thesis of 30 credits and expanding the amount of coursework correspondingly). The Master's thesis must be submitted within a deadline at the end of the fourth semester, 20 November or 1 June.

Recommended electives

It is strongly advised to take MOL100 Introduction to molecular biology. STAT200 Applied statistics is also recommended. Other courses can be chosen in agreement with supervisor.

Sequential Requirements, courses

The recommended sequence of the courses in the programme can be found under the heading "Compulsory units".

Study period abroad

You can plan study periods abroad in consultation with your supervisor as a part of the master agreement.

Teaching and learning methods

The Master thesis is a research-related piece of practical work. It requires that the student has obtained substantial knowledge within the research field.

During the 1st semester the student establishes contact with a supervisor. Together with the supervisor one will decide upon a subject for the thesis and create a schedule with an outline of courses and milestones in the thesis work.

During the master program the student will get academic supervision. The supervisor will give advice about formulations and limitations of subject and problem for the thesis, about literature, content, work progress and time consumption.

A combination of teaching methods is used in the various courses, mainly lectures and groups. You may find more information in the course descriptions.

Assessment methods

Then final step in the programme is an oral examination. The examination is held when the master's thesis is submitted, evaluated and approved.

The most common assessment methods in the courses are written and oral examination. The assessment methods for each course are described in the course description.

Grading scale

At UiB the grades are given in one of two possible grading scales: passed/failed and A to F.

The master's thesis will be graded A to F.

The grading scale for each course is given in the course description.

Diploma and Diploma supplement

The Diploma, in Norwegian, and the Diploma Supplement, in English, will be issued when the degree is completed.

Access to further studies

To be eligible for admission to the Doctoral education (PhD) the candidate must have completed a master's degree.

To qualify for the Doctoral education (PhD) at UiB the average grade for the master's thesis, the Master's degree and the bachelor's degree should be at least C.

In order to get enrolled you have to be granted a fellowship for doctoral training.

Employability

Information- and communication technology is more and more becoming a basic technology in all kinds of business activity and administration, and our candidates are strongly demanded to maintain and develop IT-systems. Many of the candidates also get employed by the IT-industry or within research and higher education.

Evaluation

The programme will be evaluated according to the quality assurance system of the University of Bergen.

Programme committee

The programme committee is responsible for the academic content, the structure and the quality of the programme.

Administrative responsibility

The Faculty of Mathematics and Natural Sciences by the Department of Informatics, holds the administrative responsibility for the programme.

Contact information

Please contact the academic adviser for the program if you have any questions:

Studierettleiar@ii.uib.no

Phone: + 47 55 58 40 25