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Course Catalog 2011-2012
SGN-6106 Computational Systems Biology, 5 cr |
Additional information
Suitable for postgraduate studies
Person responsible
Olli Yli-Harja, Juha Kesseli
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Participation in the exercises, an essay, and a learning diary. The learning diary can be replaced by a final examination.
Principles and baselines related to teaching and learning
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Learning outcomes
The student will be able to define what is computational systems biology and which subareas it covers. The student can list basic computational methods used in systems biology and use specific ready-made computational tools. The student is able to produce a summary of one of the current research topics in the field of computational systems biology.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Different types of models in systems biology (e.g. deterministic and stochastic models for cellular processes). | ||
| 2. | Mathematical and computational methods in sequence analysis and genomic expression analysis. | ||
| 3. | Possibilities of signal processing in systems biology. | ||
| 4. | Measurement techniques and effects of measurement systems in data acquisition. |
Evaluation criteria for the course
Points obtained from the requirements (exercises 20%, essay 40%, learning diary / examination 40%).
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Additional information about prerequisites
The course exercises are mainly based on Matlab and R programming. Previous knowledge on those is helpful but it is not a requirement.
Prerequisite relations (Requires logging in to POP)
Correspondence of content
There is no equivalence with any other courses
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
| The course gives an overview to different sub-areas of computational systems biology. The course presents basic computational methods and their applications in large-scale data pre-processing and analysis, biological sequence analysis, simulation methods for cellular processes, image processing for systems biology, etc. |