The literature provides strong evidence that stock prices can be predicted from past price data. Principal component analysis (PCA) is a widely used mathematical technique for dimensionality reduction and analysis of data by identifying a small number of principal components to explain the variation found in a data set. In this paper, we describe a general method for stock price prediction using covariance information, in terms of a dimension reduction operation based on principle component analysis. Projecting the noisy observation onto a principle subspace leads to a well-conditioned problem. We illustrate our method on daily stock price values for five companies in different industries. We investigate the results based on mean squared error and directional change statistic of prediction, as measures of performance, and volatility of prediction as a measure of risk. $

Colorectal cancer (CRC) is one of the most common types of cancer in world and has a high rate of mortality. The majority of cases of CRC are sporadic; however, factors such as age, a family history of inflammatory diseases, diet, lifestyle and genetics increase the risk. HOX genes and lncRNAs are two classes of genes, and alterations in the expression levels of these genes are significantly associated with numerous different types of cancer. In the present study, the expression levels of HOXC10, HOXC-AS3, HOTAIR, HOXC13 and HOXC13-AS in tumor tissues were compared with normal healthy tissues in patients with CRC. Paired tumor and normal tissues were collected from 39 patients with CRC, and reverse transcription-quantitative PCR was used the expression of HOXC-AS3, HOXC13 and HOXC10 in the tumor tissues compared with the respective normal tissues. Expression of these genes were increased in the tumor tissues compared with normal tissues; however, the difference was only significant for HOXC10. Additionally, there was a strong and significant correlation between the expression of HOTAIR and HOXC13, a moderate and significant correlation between the expression of HOTAIR and HOXC13-AS, and between HOXC13 and HOXC13-AS genes. The expression of HOXC10 was significantly higher in tumor tissues compared with the normal tissues; whereas the upregulation of HOXC-AS3 and HOXC13 were not significant. Only the correlation between the expression of HOTAIR and HOXC13 was strong and significant. As HOXC10 expression was significantly upregulated in the tumor tissues relative to normal tissues, it may serve as a biomarker for the diagnosis of CRC and as a potential therapeutic target.

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