Towards Realistic Benchmarks for MicroRNA Precursor Discovery Algorithms
| Autor: | Chun-Yi Huang, 黃駿逸 |
|---|---|
| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 MicroRNAs (miRNAs) are short non-coding RNAs (~21 – 23 nucleotides) participating in post-transcriptional regulation of gene expression. There have been many efforts on discovering miRNA precursors (pre-miRNA) over the years. Recently, ab initio approaches get more attention compared to comparative approaches because of ab initio discard sequence alignment and can discover species-specific pre-miRNAs. Because to systematically identify miRNAs from a genome by existing experimental techniques is difficult, the use of computational methods is a key factor in miRNA discovery, However, the success of ab initial approach has not been well evaluated and extended to genome-wide miRNA discovery. In this study, a systematic analysis is performed to figure out the theoretic sampling rate that makes the evaluation statistically significant. Furthermore, we proposed a approach to reduce the negative set, and successfully generate a compact set which is smaller than the theoretic size but can yield accurate performance evaluation. Considering that there are some prevailing negative sets, this study also proposes a mathematic model that can estimate the realistic performance based on those obtained with biased datasets. Finally, 5 pre-miRNA predictors are re-evaluated based on the proposed benchmarks. The experimental results show that the proposed benchmarks can helps researchers to realize and compare the realistic performance of alternative methods. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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