SGN-56007 Laboratory course in Computational Biology, 3 cr
Person responsible
Gnanavel Mutharasu, Meenakshisundaram Kandhavelu
Lessons
| Study type | Hours | Time span | Implementations | Lecture times and places |
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| SGN-56007 2015-01 |
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Requirements
To pass the course student needs to successfully complete 4 written reports (3 learning diaries and final project). The grade, from 0 to 5, will be the average of the grades of each project.
Completion parts must belong to the same implementation
Learning Outcomes
After this course, the student will be able to: - implement computational methods to solve problems involving measurement data. - perform data acquisition from raw data. - independently search for information and available methods to solve practical problems. - present results, methods and conclusions in written and oral reports.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Lecture 1 | ||
| 2. | Laboratory exercise 1 | ||
| 3. | Lecture 2 | ||
| 4. | Laboratory exercise 2 | ||
| 5. | Lecture 3 | ||
| 6. | Laboratory exercise 3 | ||
| 7. | Lecture 4 | ||
| 8. | Project work |
Instructions for students on how to achieve the learning outcomes
Active participation is required to pass the course (80%) and final project work will define the grade.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Partial passing:
Study material
| Type | Name | Author | ISBN | URL | Additional information | Examination material |
| Other online content | Detailed description of each project and the necessary tasks to be performed. | No |
Additional information about prerequisites
Basic knowledge of biology/systems biology and processing of biological signals are recommended. Skills to use Matlab are required to complete some project works.
Correspondence of content
| Course | Corresponds course | Description |
| SGN-56007 Laboratory course in Computational Biology, 3 cr | SGN-56006 Laboratory course in Information Technology for Health and Biology, 5 cr |