Support vector machine

New support vector machine-based method for microRNA target prediction

L. Li, Gao, Q., Mao, X., and Cao, Y., New support vector machine-based method for microRNA target prediction, vol. 13, pp. 4165-4176, 2014.

MicroRNA (miRNA) plays important roles in cell differentiation, proliferation, growth, mobility, and apoptosis. An accurate list of precise target genes is necessary in order to fully understand the importance of miRNAs in animal development and disease. Several computational methods have been proposed for miRNA target-gene identification. However, these methods still have limitations with respect to their sensitivity and accuracy. Thus, we developed a new miRNA target-prediction method based on the support vector machine (SVM) model.

Identifying differences in protein expression levels by spectral counting and feature selection

P. C. Carvalho, Hewel, J., Barbosa, V. C., and Yates, III, J. R., Identifying differences in protein expression levels by spectral counting and feature selection, vol. 7, pp. 342-356, 2008.

Spectral counting is a strategy to quantify relative protein concentrations in pre-digested protein mixtures analyzed by liquid chromatography online with tandem mass spectrometry. In the present study, we used combinations of normalization and statistical (feature selection) methods on spectral counting data to verify whether we could pinpoint which and how many proteins were differentially expressed when comparing complex protein mixtures.

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