YHTTAY-24486 High-throughput Data Analysis, 5 cr
Additional information
http://bioinformatics.fi/BIO4450/
Person responsible
Andre Sanches Ribeiro, Juha Kesseli
Lessons
Implementation 1: YHTTAY-24486 2015-01
| Study type | P1 | P2 | P3 | P4 | Summer |
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Requirements
Please visit: http://bioinformatics.fi/BIO4450/
Learning Outcomes
After the course, the student can: - compare sequencing and microarray technologies used in high-throughput analysis and choose suitable ones for the analysis required. - explain the principles of measurement technologies covered and how various inherent errors and biases of the measurement techniques affect the analysis. - apply common methods and algorithms to extract information from microarray and sequencing measurements. - discuss the statistical principles underlying the data analysis methods above and identify the benefits and weaknesses of each method. - select suitable algorithms for the analysis and justify the choice. - build data analysis pipelines for microarray and sequencing data analysis.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Deep sequencing technologies DNA microarrays Statistical methods for the analysis of high-throughput measurement data Data classification and clustering |
Correspondence of content
There is no equivalence with any other courses