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Articles by Yihui Liu
Total Records ( 2 ) for Yihui Liu
  Yihui Liu , Jideng Ma , Li Chen , Pengbo Lou , Jun Zhou , Mingzhou Li and Xuewei Li
  High-throughput sequencing of two small RNA libraries derived from immature (20 days old) and mature (210 day old) porcine testis samples yielded over 20 million high-quality reads. Researchers detected 461 mature microRNAs (miRNAs) encoded by 277 precursor (pre)-miRNAs of which 428 were unique. In total, 303 unique miRNAs of (428, 70.79%) were differentially expressed between immature and mature porcine testes. Compared with immature testis, 95 unique miRNAs were up-regulated and 208 unique miRNAs were down-regulated in mature testis. Strikingly, researchers found that most miRNAs and differentially expressed miRNAs were preferentially located on the X chromosome which implied their crucial roles in the sex-determination system. Furthermore, GO and KEGG analyses of the target genes that were predicted from the highly abundant differentially expressed miRNAs between mature and immature porcine testes illustrate the likely roles for these miRNAs in spermatogenesis. The study indicates that miRNAs are extensively involved in spermatogenesis and that unraveling miRNA functions in the testis will further the understanding of regulatory mechanisms of mammalian spermatogenesis and male infertility treatment.
  Yihui Liu
  It is well known that the problem arising from high dimensionality of data should be considered in pattern recognition. Original microarray data are usually of high dimensionality, whereas, only limited training samples are available. Therefore, dimensionality reduction is an important strategy to greatly improve the classification performance of microarray data. A novel method of feature extraction and dimensionality reduction for high-dimensional microarray data is proposed in this study. A set of orthogonal wavelet detail coefficients based on wavelet decomposition at different levels is extracted to characterize the localized features of microarray data. Experiments are carried out on four datasets. A highly competitive accuracy is achieved in comparison with the performance of other models.
 
 
 
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