| 講 題： |
Principal component analysis based unsupervised feature extraction applied to bioinformatics analysis |
| 演講者： |
Professor Y-h. Taguchi ( Department of Physics, Chuo University, Japan) |
| 時 間： |
105年10月28日（星期五）10：40 - 12：00 （上午10：20 - 10：40茶會於統計所821室舉行） |
| 地 點： |
綜合三館837室 |
| 摘 要： |
In bioinformatics analysis, it is very usual that features (genes) are more than samples. In this case, reduction of features is critical to analyze data. Although there were many complicated procedures proposed, recently we found that principal component analysis (PCA) can be successfully used for this purpose. Featured placed as outliers in the embedding turn out to be critical for bioinfotmatics analysis. We will show some of recent results using this methodology including miRNA-mRNA interaction from expression analysis. |