A forecasting of stock trading price using time series information based on big data

Big data is a large set of structured or unstructured data that can collect, store, manage, and analyze data with existing database management tools. And it means the technique of extracting value from these data and interpreting the results. Big data has three characteristics: The size of existing data and other data (volume), the speed of data generation (velocity), and the variety of information forms (variety). The time series data are obtained by collecting and recording the data generated in accordance with the flow of time. If the analysis of these time series data, found the characteristics of the data implies that feature helps to understand and analyze time series data. The concept of distance is the simplest and the most obvious in dealing with the similarities between objects. The commonly used and widely known method for measuring distance is the Euclidean distance. This study is the result of analyzing the similarity of stock price flow using 793,800 closing prices of 1,323 companies in Korea. Visual studio and Excel presented calculate the Euclidean distance using an analysis tool. We selected “000100” as a target domestic company and prepared for big data analysis. As a result of the analysis, the shortest Euclidean distance is the code “143860” company, and the calculated value is “11.147”. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested

Pathology of C3 Glomerulopathy

C3 glomerulopathy is a renal disorder involving dysregulation of alternative pathway complement activation. In most instances, a membranoproliferative pattern of glomerular injury with a prevalence of C3 deposition is observed by immunofluorescence microscopy. Dense deposit disease (DDD) and C3 glomerulonephritis (C3GN) are subclasses of C3 glomerulopathy that are distinguishable by electron microscopy. Highly electron-dense transformation of glomerular basement membrane is characteristic of DDD. C3GN should be differentiated from post-infectious glomerulonephritis and other immune complex-mediated glomerulonephritides showing C3 deposits

Arrayed CRISPR screen with image-based assay reliably uncovers host genes required for coxsackievirus infection

Pooled CRISPR screens based on lentiviral systems have been widely applied to identify the effect of gene knockout on cellular phenotype. Although many screens were successful, they also have the limitation that genes conferring mild phenotypes or those essential for growth can be overlooked, as every genetic perturbation is incorporated in the same population. Arrayed screens, on the other hand, incorporate a single genetic perturbation in each well and could overcome these limitations. However, arrayed screens based on siRNA-mediated knockdown were recently criticized for low reproducibility caused by incomplete inhibition of gene expression. To overcome these limitations, we developed a novel arrayed CRISPR screen based on a plasmid library expressing a single guide RNA (sgRNA) and disrupted 1514 genes, encoding kinases, proteins related to endocytosis, and Golgi-localized proteins, individually using 4542 sgRNAs (three sgRNAs per gene). This screen revealed host factors required for infection by coxsackievirus B3 (CVB3) from Picornaviridae, which includes human pathogens causing diverse diseases. Many host factors that had been overlooked in a conventional pooled screen were identified for CVB3 infection, including entry-related factors, translational initiation factors, and several replication factors with different functions, demonstrating the advantage of the arrayed screen. This screen was quite reliable and reproducible, as most genes identified in the primary screen were confirmed in secondary screens. Moreover, ACBD3, whose phenotype was not affected by siRNA-mediated knockdown, was reliably identified. We propose that arrayed CRISPR screens based on sgRNA plasmid libraries are powerful tools for arrayed genetic screening and applicable to larger-scale screens.

Arrayed CRISPR screen with image-based assay reliably uncovers host genes required for coxsackievirus infection

Pooled CRISPR screens based on lentiviral systems have been widely applied to identify the effect of gene knockout on cellular phenotype. Although many screens were successful, they also have the limitation that genes conferring mild phenotypes or those essential for growth can be overlooked, as every genetic perturbation is incorporated in the same population. Arrayed screens, on the other hand, incorporate a single genetic perturbation in each well and could overcome these limitations. However, arrayed screens based on siRNA-mediated knockdown were recently criticized for low reproducibility caused by incomplete inhibition of gene expression. To overcome these limitations, we developed a novel arrayed CRISPR screen based on a plasmid library expressing a single guide RNA (sgRNA) and disrupted 1514 genes, encoding kinases, proteins related to endocytosis, and Golgi-localized proteins, individually using 4542 sgRNAs (three sgRNAs per gene). This screen revealed host factors required for infection by coxsackievirus B3 (CVB3) from Picornaviridae, which includes human pathogens causing diverse diseases. Many host factors that had been overlooked in a conventional pooled screen were identified for CVB3 infection, including entry-related factors, translational initiation factors, and several replication factors with different functions, demonstrating the advantage of the arrayed screen. This screen was quite reliable and reproducible, as most genes identified in the primary screen were confirmed in secondary screens. Moreover, ACBD3, whose phenotype was not affected by siRNA-mediated knockdown, was reliably identified. We propose that arrayed CRISPR screens based on sgRNA plasmid libraries are powerful tools for arrayed genetic screening and applicable to larger-scale screens.