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Recent studies show that drug-disease associations provide important information for drug discovery and drug repositioning. Wet experimental identification of drug-disease associations is time-consuming and labor-intensive. Therefore, the development of computational methods that predict drug-disease associations is an urgent task. In this paper, we propose a novel computational method named NTSIM,...
human splicing branchpoints are functional elements of the alternative splicing, and the study on branchpoints can help to understand the mechanism of human pre-mRNA transcript. There are a large number of human splicing branchpoints, but the wet methods that identify branchpoints are labor-intensive and time-consuming. In this paper, we utilize machine learning techniques to build models for the...
The prediction of T-cell epitopes is of great help for facilitating vaccine design and understanding the immune system. In the bioinformatics, the MHC-binding peptides are defined as the T-cell epitopes, which will trigger the immune response to the antigens. However, binding peptides cannot necessarily activate the immune response, namely non-immunogenic. Until now, little attention has been paid...
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