Methods in molecular biology
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microRNAs (miRNAs) are central regulators of gene expression. They are actively studied for their involvement in numerous physiological and pathological conditions but also as diagnostic biomarkers or promising therapeutic targets. The increased complexity of the miRNA interactomes hinders straightforward interpretation of miRNA expression differences between states and conditions. ⋯ The most commonly utilized databases and algorithms include DIANA-microT-CDS, DIANA-TarBase v7.0, DIANA-lncBase v2.0, DIANA-miRGen v3.0, DIANA-miRPath v3.0, and DIANA-mirExTra v2.0. In the presented protocol, we will utilize different online tools in order to explore miRNA functions and to identify probable targets of interest for downstream analyses and wet lab experiments. The combined use of different applications from the DIANA suite can shed light to numerous different aspects of miRNA regulation and regulatory function, without the necessity for extensive bioinformatics expertise or computational infrastructure.
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Cell signaling and functions heavily rely on post-translational modifications (PTMs) of proteins. Their high-throughput characterization is thus of utmost interest for multiple biological and medical investigations. ⋯ However, the large and complex datasets produced pose multiple data interpretation challenges, ranging from spectral interpretation to statistical and multivariate analyses. Here, we present a typical workflow to interpret such data.
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Comparative profiling proteomics experiments are important tools in biological research. In such experiments, tens to hundreds of thousands of peptides are measured simultaneously, with the goal of inferring protein abundance levels. ⋯ Previously we have reported the non-normal distribution of SILAC datasets, and demonstrated the permutation test to be a superior method for the statistical evaluation of non-normal peptide ratios. This chapter outlines the steps and the R scripts that can be used for performing permutation analysis with false discovery rate control via the Benjamini-Yekutieli method.
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Recent advances in mass spectrometry based proteomic techniques and publicly available large proteomic repositories are being exploited to characterize the proteome of multiple organisms. While humongous amount of proteomic data is being acquired and analyzed, many biological questions still remain unanswered. Proteotypic peptides which uniquely represent target proteins or a protein isoform are used as an alternative strategy for protein identification in the field of immunological methods and targeted proteomic techniques. Using different computational approaches, resources and techniques used in the identification of proteotypic peptides of target proteins is discussed here.
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Normal cellular functioning is maintained by macromolecular machines that control both core and specialized molecular tasks. These machines are in large part multi-subunit protein complexes that undergo regulation at multiple levels, from expression of requisite components to a vast array of post-translational modifications (PTMs). ⋯ Here we provide a framework for systematically studying these PTMs in the context of global protein-protein interaction networks. This analytical framework allows insight into which functions specific PTMs tend to cluster in, and furthermore which complexes either single or multiple PTM signaling pathways converge on.