Wyniki wyszukiwania - BazTech

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Exploring Baltic Sea cyanobacteria for small-molecule inhibitors of microRNA function: a project description

Brzuzan P., Mazur-Marzec H., Stefaniak F., Woźny M., Florczyk M.

Environmental Biotechnology

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2018

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Vol. 14, No. 1

1--4

EN

Cyanobacteria constitute a rich source of biologically active and structurally diverse compounds. The pharmacological potential of these compounds resides among others in their ability to control the proliferation and growth of cancer cell lines and potent disease-causing microbial agents. Despite recent scientific advances, the way these compounds interact with the body’s molecular structure are still unclear and science still has to discover how the cyanobacterial metabolites interact with cell structures and how cells react to them. In this project, we will study yet unexamined cyanobacterial metabolites, especially the compounds which act as chemical ligands for microRNA (miRNA) -binding sites, making them promising regulators (inhibitors) of gene networks that are involved in various diseases. We will first develop a stable cell line that constitutively expresses a unique miRNA reporter system. Then, we will conduct a screen on chemical compounds discovered in Baltic cyanobacteria to identify small molecules with inhibitory activity and specificity to MIR92b-3p, which has a significant impact on liver cell behavior in humans. We assume that a successful MIR92b-3p inhibitor will bind to the precursors of MIR92b-3p miRNA, disabling the action of either of the two processing enzymes involved in the biogenesis of any miRNA in a cell (Drosha or Dicer), thus affecting the MIR92b function. The discoveries made with these inhibitory chemical molecules could provide insight into the role of the MIR92 pathway in liver diseases and cancer, and possibly, if promising results appear, they may facilitate a strategy for treating some human diseases in the future.

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Modified S-transform as a tool to identify secondary structure elements in RNA

Singh N., Sharma S. D., Yennamalli R. M.

Bio-Algorithms and Med-Systems

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2017

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Vol. 13, no. 4

182--193

EN

In this article, we describe the applicability of a signal processing method, specifically the modified S-transform (MST) method, on RNA sequences to identify periodicities between 2 and 11. MicroRNAs (miRNA) are associated with gene regulation and gene silencing and thus have wide applications in biological sciences. Also, the functionality of miRNA is highly associated with its secondary structures (stem, bulge and loop). Signal processing methods have been previously applied on genomic data to reveal the periodicities that determine a wide variety of biological functions, ranging from exon detection to microsatellite identification in DNA sequences. However, there has been less focus on RNA-based signal processing. Here, we show that the signal processing method can be successfully applied to miRNA sequences. We observed that these periodicities are highly correlated with the secondary structure of miRNA and such methods could possibly be used as indicators of secondary and tertiary structure formation.

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MicroRNA expression prediction: Regression from regulatory elements

Oğul H., Tuncer M. E.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 1

89--94

EN

MicroRNAs are known as important actors in post-transcriptional regulation and relevant biological processes. Their expression levels do not only provide information about their own activities but also implicitly explain the behaviors of their targets, thus, in turn, the circuitry of underlying gene regulatory network. In this study, we consider the problem of estimating the expression of a newly discovered microRNA with known promoter sequence in a certain condition where the expression values of some known microRNAs are available. To this end, we offer a regression model to be learnt from the expression levels of other microRNAs obtained through a microarray experiment. To our knowledge, this is the first study that evaluates the predictability of microRNA expression from the regulatory elements found in its promoter sequence. The results obtained through the experiments on real microarray data justify the applicability of the framework in practice.