Current Issue : January - March Volume : 2021 Issue Number : 1 Articles : 5 Articles
Background: Drug-target interaction prediction is of great significance for narrowing\ndown the scope of candidate medications, and thus is a vital step in drug discovery.\nBecause of the particularity of biochemical experiments, the development of new\ndrugs is not only costly, but also time-consuming. Therefore, the computational\nprediction of drug target interactions has become an essential way in the process of\ndrug discovery, aiming to greatly reducing the experimental cost and time....
Background: Glioblastoma multiforme (GBM) is one of the most common malignant\nbrain tumors and its average survival time is less than 1 year after diagnosis.\nResults: Firstly, this study aims to develop the novel survival analysis algorithms to\nexplore the key genes and proteins related to GBM. Then, we explore the significant\ncorrelation between AEBP1 upregulation and increased EGFR expression in primary\nglioma, and employ a glioma cell line LN229 to identify relevant proteins and\nmolecular pathways through protein network analysis. Finally, we identify that AEBP1\nexerts its tumor-promoting effects by mainly activating mTOR pathway in Glioma....
Background: High-dimensional flow cytometry and mass cytometry allow\nsystemic-level characterization of more than 10 protein profiles at single-cell resolution\nand provide a much broader landscape in many biological applications, such as disease\ndiagnosis and prediction of clinical outcome. When associating clinical information\nwith cytometry data, traditional approaches require two distinct steps for identification\nof cell populations and statistical test to determine whether the difference between\ntwo population proportions is significant. These two-step approaches can lead to\ninformation loss and analysis bias....
Background: Protein microarray is a well-established approach for characterizing\nactivity levels of thousands of proteins in a parallel manner. Analysis of protein\nmicroarray data is complex and time-consuming, while existing solutions are either\noutdated or challenging to use without programming skills. The typical data analysis\npipeline consists of a data preprocessing step, followed by differential expression\nanalysis, which is then put into context via functional enrichment. Normally, biologists\nwould need to assemble their own workflow by combining a set of unrelated tools to\nanalyze experimental data. Provided that most of these tools are developed\nindependently by various bioinformatics groups, making them work together could be\na real challenge....
Background: Resolution estimation is the main evaluation criteria for the\nreconstruction of macromolecular 3D structure in the field of cryoelectron microscopy\n(cryo-EM). At present, there are many methods to evaluate the 3D resolution for\nreconstructed macromolecular structures from Single Particle Analysis (SPA) in cryo-EM\nand subtomogram averaging (SA) in electron cryotomography (cryo-ET). As global\nmethods, they measure the resolution of the structure as a whole, but they are\ninaccurate in detecting subtle local changes of reconstruction. In order to detect the\nsubtle changes of reconstruction of SPA and SA, a few local resolution methods are\nproposed. The mainstream local resolution evaluation methods are based on local\nFourier shell correlation (FSC), which is computationally intensive. However, the\nexisting resolution evaluation methods are based on multi-threading implementation\non a single computer with very poor scalability....
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