NBIA05008U Biological Sequence Analysis
MSc Programme in Biochemistry
MSc Programme in Bioinformatics
MSc Programme in Biology
MSc Programme in Biology with a minor subject
MSc Programme in Molecular Biomedicine
The course covers the fundamental theoretical background for biological sequence analysis as well as applications of the methods, which are learned through homework and exercises. The topics include
- Alignment methods for biological sequences (DNA, RNA, proteins)
- Methods for searching sequence databases, including deep learning approaches
- Hidden Markov models with applications
- Motif finding and discovery
- Mapping and assembly of DNA sequencing data
- The knowledge and skills acquired in this course will enable the students to understand and develop state-of-the-art algorithms.
Knowledge: The student will:
- know the field of biological sequence analysis
- know and understand the main algorithms and methods used in
- pairwise and multiple alignment
- searching of sequence databases
- hidden Markov models of biological sequences
- finding and discovery of motifs in biological sequences
- mapping and assembly of DNA sequencing data
- understand the biological contexts in which to apply biological sequence analysis
Skills: The student will be able to:
- derive simple probabilistic methods and algorithms for biological sequence analysis
- explain the algorithms and methods covered in the course
- interpret results of standard methods used in biological sequence analysis
- select the proper sequence analysis methods and tools for a given biological problem
- run some standard computer programs for biological sequence analysis
Competences: The student will obtain these general
competences:
- Will be able to discuss and explain methods in biological sequence analysis with researchers in bioinformatics and related sciences
- Will be able to contribute to interdisciplinary projects involving biological sequence analysis
- Will be able to read, understand, and discuss scientific literature in biological sequence analysis
See Absalon.
Academic qualifications equivalent to a BSc degree is recommended.
- Category
- Hours
- Lectures
- 40
- Preparation
- 141
- Practical exercises
- 24
- Exam
- 1
- Total
- 206
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 30 minutes (30-minute preparation time)
- Aid
- Written aids allowed
The use of Large Language Models (LLM)/Large Multimodal Models (LMM) – such as ChatGPT and GPT-4 – is permitted during the preparation time.
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
- Re-exam
Same as the ordinary exam
Criteria for exam assesment
In order to obtain the grade 12 the student should convincingly and accurately demonstrate the knowledge, skills and competences described under Learning Outcome.
Course information
- Language
- English
- Course code
- NBIA05008U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- A
- Course capacity
- 60
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Study board
- Study Board for the Biological Area
Contracting departments
- Department of Biology
- Department of Nutrition, Exercise and Sports
Contracting faculty
- Faculty of Science
Course Coordinators
- Amelie Stein (amelie.stein@bio.ku.dk)
Lecturers
Anders Krogh
Jeppe Vinther