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<p>DNA-binding proteins (DBPs) play a critical role in the development of drugs for treating genetic diseases and in DNA biology research. It is essential for predicting DNA-binding proteins more accurately and efficiently. In this paper, a Laplacian Local Kernel Alignment-based Restricted Kernel Machine (LapLKA-RKM) is proposed to predict DBPs. In detail, we first extract features from the protein sequence using six methods. Second, the Radial Basis Function (RBF) kernel function is utilized to construct pre-defined kernel metrics. Then, these metrics are combined linearly by weights calculated by LapLKA. Finally, the fused kernel is input to RKM for training and prediction. Independent tests and leave-one-out cross-validation were used to validate the performance of our method on a small dataset and two large datasets. Importantly, we built an online platform to represent our model, which is now freely accessible via <ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://8.130.69.121:8082/">http://8.130.69.121:8082/</ext-link>.</p>
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In order to solve the problem of insufficient capital adequacy, haphazard internal control, the lower international competitiveness and others, the domestic commercial banks have introduced strategic investors. In order to study whether efficiency of introducing the strategic investors is improved, this paper carries out panel data regression analysis, using data of such banks as: the China Construction Bank, Agricultural Bank and other 9 banks which have already introduced strategic investors. Then, the result shows that although the introduction of strategic investors for bank profitability is not significant. It is conducive to improve the bank's financial innovation ability, cost control ability and risk management capabilities in the overall performance of bank efficiency; and with the increasing investment and shareholding ratios in strategic investors, the beneficial effect to improve the efficiency of China's commercial banks becomes more obvious. On the basis of empirical research, this article puts forward some suggestions in the management and introduction of strategic investors.
Improving enterprises’ independent innovation capability is critical to improving their competitive strength, industries’ independent innovation capability, industries’ international competitiveness, and countries’ independent innovation capability, as well as building an innovative country. It is now the era of strategic innovation. Many growing businesses are focused on strategic innovation, but they overlook the issue of ensuring that strategic innovation is implemented. Management and innovation are perennial themes in the long-term development of businesses. The most pressing issue in enterprises’ strategic innovation activities is how to combine their strategic direction with their superior ability and choose a strategic innovation path that is appropriate for their development. This paper uses data mining theory to establish the K-means clustering algorithm to identify the best strategic orientation of enterprise innovation strategic direction selection based on the existing advantages and capabilities of enterprises based on the analysis of the direction of enterprise strategic innovation.
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