Course responsible:Lars Gustav Snipen
Campus / Online:Taught campus Ås
Teaching language:Engelsk, norsk
Limits of class size:60
Course frequency:Odd years
Nominal workload:70 hours with instructor present: 180 hours self study
Teaching and exam period:This course starts in autumn parallel. This course has teaching/evaluation in autumn parallel.
About this course
Modern sequencing technology, shotgun and amplicon sequencing. Assembly and annotations of genomes and metagenomes. Comparative genomics and metagenomics. Analyses of data from microbial communities. Use of High Performance Computing facilities.
Competence in Bioinformatics contributes to all UN goals for sustainable development that involves biology (health, hood, nature).
KNOWLEDGE: The ideas behind commonly used algorithms for processing and analysis of sequence data. Get to know a UNIX computing cluster and simple shell scripting. Know some common statistical methods for metagenome-studies and apply these on real data using R and R-packages.
SKILLS: Be able to apply elements from the topics above to solve project assignments in the course. Making simple shell-scripts and R-scripts and run heavier analyses on a UNIX computing cluster. Present material both orally and in a written report.
GENERAL COMPETENCE: Be able to make use of, and understand, the future computational pipelines of (meta)genome studies. Practical programming competence, directed toward analysis og bio-data.
- The basis for the course is a series of written material as markdown documents as well as a number of screencasts. All physical teaching will be at weekly hours used for discussions and solutions to exercises as well as simple lectures over certain topics of special interest. There will also be oral presentations over some project reports.
- Active use of Canvas.
Introduction to bioinformatics (BIN210) - Some knowledge of modern sequencing - Basics on sequence alignments, pairwise, multiple, database search (BLAST) - Basics on phylogeni
Introduction to statistics (STAT100) - Familiar with stochastic variables and parameters - Basic calculus of probability, conditional probabilities
Introduction to programming (STIN100) - Be familiar with datatypes numeric, character, logical, factor - Be familiar with data structures vector (array), matrix, table (tibble/data.frame), list - Be familiar with concepts like loops and functions/methods
No advanced coding will be required, but we have no time for general teaching in coding. All coding will be in R and shell (bash).
- Programming and statistics beyond the introductory level.
- Portfolio asessment. Several project assignments will be given, and all must be passed in order to pass the course.
- External examiner will approve the projects and evaluate a selection of them
- Students must bring their own laptop to computer-labs.
- 6 hours teaching activities per week. This is a mixture of lectures, hand-on exercises and solving problems in Groups.
- M-BIAS, M-BIOTEK, M-KB
- Passed / Not Passed
- Special requirements in Science