- author = "Pal Saetrom and Ola {Snove, Jr.}",
- title = "A comparison of siRNA efficacy predictors",
- journal = "Biochemical and Biophysical Research Communications",
- year = "2004",
- volume = "321",
- pages = "247--253",
- number = "1",
- abstract = "Short interfering RNA (siRNA) efficacy prediction algorithms aim to increase the probability of selecting target sites that are applicable for gene silencing by RNA interference. Many algorithms have been published recently, and they base their predictions on such different features as duplex stability, sequence characteristics, mRNA secondary structure, and target site uniqueness. We compare the performance of the algorithms on a collection of publicly available siRNAs. First, we show that our regularised genetic programming algorithm GPboost appears to have a higher and more stable performance than other algorithms on the collected datasets. Second, several algorithms gave close to random classification on unseen data, and only GPboost and three other algorithms have a reasonably high and stable performance on all parts of the dataset. Third, the results indicate that the siRNAs' sequence is sufficient input to siRNA efficacy algorithms, and that other features that have been suggested to be important may be indirectly captured by the sequence.",
- owner = "wlangdon",
-
URL = "
http://www.sciencedirect.com/science/article/B6WBK-4CW546Y-S/2/1c4d9091ea50571084790a39c8ff0b81",
- month = "13 " # aug,
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
10.1016/j.bbrc.2004.06.116",
-
notes = "PMID: 15358242
Cited by Demonstration of two novel methods for predicting functional siRNA efficiency Peilin Jia, Tieliu Shi, Yudong Cai, and Yixue Li BMC Bioinformatics. 2006; 7: 271. Published online 2006 May 29. doi:10.1186/1471-2105-7-271. PMCID: PMC1524998",
