Courses: BINF301 Genome-scala algorithms - Autumn 2020
Level of Study
Master
Language of Instruction
English
Teaching semester
Spring. Runs first time spring 2020.
Place of Instruction
Objectives and Content
Will be offered for the first time spring 2020
The course covers advanced algorithms used for analysis of biological sequences with a focus on algorithms specialized for analysis of data produced by high-throughput technologies. The course includes use of indexing methods and related data structures including the de-Bruijn graphs, Burrows-Wheeler transform and related algorithms. The course also goes into use of such methods for de-novo sequence assembly, analysis of DNA resequencing data, and various other applications including ChIP-seq, ATAC-seq and bisulphite-sequencing. The course also includes methods for analysis of third-generation long read sequencing and single-cell sequencing technologies.
Learning Outcomes
On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge, skills and general competence
The student
- Understands and is able to implement algorithms for analysis of high-throughput sequencing data including de-novo assembly, de-Bruijn graphs, Burrows-Wheeler alignment
- Understands and is able to design and choose approaches to analyze data from various applications of sequencing including ChIP-seq, ATAC-seq
- Has a general understanding of third-generation technologies for sequencing and the data produced
Required Previous Knowledge
INF100
Recommended Previous Knowledge
Be able to implement basic algorithms in a programming language of your own choice. A basic understanding of algorithms and efficiency, as well as statistics, is required. Good background within algorithms is recommended, at least corresponding to INF102. In addition, a good background in bioinformatics is recommended, corresponding to BINF100, BINF200, and BINF201.
Credit Reduction due to Course Overlap
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
The course is given as 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 semester
Forms of Assessment
The forms of assessment are:
- Mandatory exercises, 50 % of total grade.
- Due to coronavitus situation the exam will be digital oral examination, 50% of total grade.
All compulsory assignments must be approved before examination.
Examination Support Material
Non-programmable calculator, according to the faculty regulations
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 June 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.
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 mailto:studieveileder@ii.uib.noStudent 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.
Contact Information
Student adviser:
mailto:studieveileder@ii.uib.noStudent adviser
T: 55 58 42 00