miRror-Suite

The miRror application provides insights on microRNA (miRNA) regulation. It is based on the notion of a combinatorial regulation by an ensemble of miRNAs or genes. miRror integrates predictions from a dozen of miRNA resources that are based on complementary algorithms into a unified statistical framework. For miRNAs set as input, the online tool provides a ranked list of targets, based on set of resources selected by the user, according to their significance of being coordinately regulated. Symmetrically, a set of genes can be used as input to suggest a set of miRNAs. The user can restrict the analysis for the preferred tissue or cell line. miRror is suitable for analyzing results from miRNAs profiling, proteomics and gene expression arrays.
http://www.proto.cs.huji.ac.il/mirror[1]

microRNAs (miRNAs) are short, noncoding RNAs that negatively regulate the levels of mRNA post-transcriptionally. Recent experiments revealed thousands of mRNA-miRNA pairs in which multiple miRNAs may bind the same transcript. These results raised the notion of miRNAs teamwork for a wide range of cellular context. miRror2.0 utilizes the miRNA-target predictions from over a dozen programs and resources and unifies them under a common statistical basis. The platform, called miRror2.0, considers the combinatorial regulation by miRNAs in different tissues, cell lines and under a broad range of conditions. A flexible setting permits the selection of the preferred combination of miRNA-target prediction resources as well as the statistical parameters for the analysis. miRror2.0 covers six major model organisms including human and mouse. Importantly, the system is capable of analyzing hundreds of genes that were subjected to miRNAs' regulation. Activating miRror2.0 by introducing thousands of genes from miRNA overexpression experiments successfully identified the objective miRNAs. The output from miRror2.0 is a list of genes that is optimally regulated by a defined set of miRNAs. A symmetric application of miRror2.0 starts with a set of miRNAs, and the system then seeks the preferred set of genes that are regulated by that miRNA composition. The results from miRror2.0 are empowered by an iterative procedure called PSI-miRror. PSI-miRror tests the robustness of miRror2.0 prediction. It allows a refinement of the initial list of genes in view of the miRNAs that optimally regulate this list. We present miRror2.0 as a valuable resource for supporting cellular experimentalists that seek recovery of combinatorial regulation by miRNAs from noisy experimental data. miRror2.0 is available at http://www.mirrorsuite.cs.huji.ac.il .[2]

MicroRNAs (miRNAs) are short, non-coding RNAs that negatively regulate post-transcriptional mRNA levels. Recent data from cross-linking and immunoprecipitation technologies confirmed the combinatorial nature of the miRNA regulation. We present the miRror-Suite platform, developed to yield a robust and concise explanation for miRNA regulation from a large collection of differentially expressed transcripts and miRNAs. The miRror-Suite platform includes the miRror2.0 and Probability Supported Iterative miRror (PSI-miRror) tools. Researchers who performed large-scale transcriptomics or miRNA profiling experiments from cells and tissues will benefit from miRror-Suite. Our platform provides a concise, plausible explanation for the regulation of miRNAs in such complex settings. The input for miRror2.0 may include hundreds of differentially expressed genes or miRNAs. In the case of miRNAs as input, the algorithm seeks the statistically most likely set of genes regulated by this input. Alternatively, for a set of genes, the miRror algorithm seeks a collection of miRNAs that best explains their regulation. The miRror-Suite algorithm designates statistical criteria that were uniformly applied to a dozen miRNA-target prediction databases. Users select the preferred databases for predictions and numerous optional filters/parameters that restrict the search to the desired tissues, cell lines, level of expression and predictor scores. PSI-miRror is an advanced application for refining the input set by gradually enhancing the degree of pairing of the sets of miRNAs with the sets of targets. The iterations of PSI-miRror probe the interlinked nature of miRNAs and targets within cells. miRror-Suite serves experimentalists in facilitating the understanding of miRNA regulation through combinatorial-cooperative activity. The platform applies to human, mouse, rat, fly, worm and zebrafish. Database URL: http://www.mirrorsuite.cs.huji.ac.il.[3]

MicroRNAs (miRNAs) negatively regulate the levels of messenger RNA (mRNA) post-transcriptionally. Recent advances in CLIP (cross-linking immunoprecipitation) technology allowed capturing miRNAs with their cognate mRNAs. Consequently, thousands of validated mRNA-miRNA pairs have been revealed. Herein, we present a comprehensive outline for the combinatorial regulation by miRNAs. We implemented combinatorial and statistical constraints in the miRror2.0 algorithm. miRror estimates the likelihood of combinatorial miRNA activity in explaining the observed data. We tested the success of miRror in recovering the correct miRNA from 30 transcriptomic profiles of cells overexpressing a miRNA, and to identify hundreds of genes from miRNA sets, which are observed in CLIP experiments. We show that the success of miRror in recovering the miRNA regulation from overexpression experiments and CLIP data is superior in respect to a dozen leading miRNA-target prediction algorithms. We further described the balance between alternative modes of joint regulation that are executed by pairs of miRNAs. Finally, manipulated cells were tested for the possible involvement of miRNA in shaping their transcriptomes. We identified instances in which the observed transcriptome can be explained by a combinatorial regulation of miRNA pairs. We conclude that the joint operation of miRNAs is an attractive strategy to maintain cell homeostasis and overcoming the low specificity inherent in individual miRNA-mRNA interaction.[4]

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