Koutounidis, Antonios (2018) Analysis of gene expression data of tumor vs. normal cells in clear cell Renal Cell Carcinoma. Bachelor's Thesis, Computing Science.
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Abstract
The last years as more and more reliable cancer data sets become available and more researchers work on them, the way that a drug is produced is changing. Knowledge about the mechanisms of a disease can be acquired from those data sets. Based on a resent analysis of gene expression data which addressed the prediction of recurrence risk in patients with clear cell Renal Cell Carcinoma, we study in more detail the classification problem, whether a sample is healthy or unhealthy. Using a GMLVQ classifier we observe that even a simple classifier trained by a significant small number of random genes can achieve great results in respect of performance. At the end we show that, even the information to classify a sample as healthy or unhealthy is spread on many genes, still there is a level of significance between the genes.
| Item Type: | Thesis (Bachelor's Thesis) |
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| Supervisor name: | Biehl, M. |
| Degree programme: | Computing Science |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 14 Sep 2018 |
| Last Modified: | 26 Sep 2018 08:40 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/18576 |
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