miRNA

imDC: an ensemble learning method for imbalanced classification with miRNA data

C. Y. Wang, Hu, L. L., Guo, M. Z., Liu, X. Y., and Zou, Q., imDC: an ensemble learning method for imbalanced classification with miRNA data, vol. 14, pp. 123-133, 2015.

Imbalances typically exist in bioinformatics and are also common in other areas. A drawback of traditional machine learning methods is the relatively little attention given to small sample classification. Thus, we developed imDC, which uses an ensemble learning concept in combination with weights and sample misclassification information to effectively classify imbalanced data. Our method showed better results when compared to other algorithms with UCI machine learning datasets and microRNA data.

Establishment of a prediction model for the miRNA-based heading date characteristics of rice in the booting stage

Y. C. Chen, Lin, W. S., Chen, R. K., Chao, Y. Y., Chin, S. W., Chen, F. C., and Lee, C. Y., Establishment of a prediction model for the miRNA-based heading date characteristics of rice in the booting stage, vol. 14, pp. 4381-4390, 2015.

Rice (Oryza sativa L.) is one of the most important food crops in the world. In Taiwan, due to the warm climate, there are two harvests annually. However, the yield and quality of rice can vary between each crop season in any given year. Previous reports have shown that microRNAs (miRNAs) play a crucial role in many developmental and physiological processes in plants. In this study, the heading date characteristics of 167 rice cultivars from the second crop season were recorded, and 27 rice cultivars were selected for preliminary microarray analysis.

Suitable internal control microRNA genes for measuring miRNA abundance in pig milk during different lactation periods

Y. R. Gu, Liang, Y., Gong, J. J., Zeng, K., Li, Z. Q., Lei, Y. F., He, Z. P., and Lv, X. B., Suitable internal control microRNA genes for measuring miRNA abundance in pig milk during different lactation periods, vol. 11. pp. 2506-2512, 2012.

Determination of an optimal set/number of internal control microRNA (miRNA) genes is a critical, but often undervalued, detail of quantitative gene expression analysis. No validated internal genes for miRNA quantitative PCR (q-PCR) in pig milk were available. We compared the expression stability of six porcine internal control miRNA genes in pig milk from different lactation periods (1 h, 3 days, 7 days, 14 days, 21 days, and 28 days postpartum), using an EvaGreen q-PCR approach.

Identification and abundance of miRNA in chicken hypothalamus tissue determined by Solexa sequencing

G. R. Sun, Li, M., Li, G. X., Tian, Y. D., Han, R. L., and Kang, X. T., Identification and abundance of miRNA in chicken hypothalamus tissue determined by Solexa sequencing, vol. 11, pp. 4682-4694, 2012.

We used Solexa sequencing technology to identify and determine the abundance of miRNAs and compared the characteristics and expression patterns of miRNA of 1-day-old and 36-week-old chicken hypothalamuses. We obtained 17,825,753 and 10,928,745 high-quality reads from 36-week-old and 1-day-old chickens, respectively. Three hundred and seventy-one conserved miRNAs were expressed in both libraries. Among the conserved miRNAs, 22 miRNAs were up-regulated and 157 miRNAs were down-regulated in the 36-week-old chicken hypothalamus tissues.

Meta-analysis of association of common variants in the KCNJ11-ABCC8 region with type 2 diabetes

L. J. Qin, Lv, Y., and Huang, Q. Y., Meta-analysis of association of common variants in the KCNJ11-ABCC8 region with type 2 diabetes, vol. 12, pp. 2990-3002, 2013.

KCNJ11 (potassium inwardly rectifying channel, subfamily J, member 11) and ABCC8 (ATP-binding cassette, subfamily C (CFTR/MRP), member 8) have been studied for association with type 2 diabetes in various ethnic populations with contradictory results. We performed a comprehensive meta-analysis for KCNJ11 rs5219, rs5210, rs5215, and ABCC8 rs757110 to evaluate the effect of these regions on genetic susceptibility for type 2 diabetes.

Expression profile analysis reveals putative prostate cancer-related microRNAs

H. Song, Liu, Y., Pan, J., and Zhao, S. T., Expression profile analysis reveals putative prostate cancer-related microRNAs, vol. 12, pp. 4934-4943, 2013.

Annotation of prostate cancer (PC) genomes provides a foundation for discoveries that can improve the understanding and treatment of the disease. Therefore, in the present study, we used the Student t-test to identify differentially expressed PC-related mRNAs and microRNAs (miRNAs). Then, we performed interrelated mapping of miRNA target genes between abnormally expressed mRNAs and miRNAs, and explored mRNA-target miRNA interrelated pairs to explain the biological functions of miRNA during the progression of PC, thus revealing the occurrence of miRNA-mediated PC.

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