mrsFAST
Abstract is not available.[1]
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Mouse
tfmirloop
Transcription factors (TFs) have long been known to be principally activators of transcription in eukaryotes and prokaryotes. The growing awareness of the ubiquity of microRNAs (miRNAs) as suppressive regulators in eukaryotes, suggests the possibility of a mutual, preferential, self-regulatory connectivity between miRNAs and TFs. Here we investigate the connectivity from TFs and miRNAs to other genes and each other using text mining, TF promoter binding site and 6 different miRNA binding site prediction methods.
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MiRTif
MicroRNAs (miRNAs) are a set of small non-coding RNAs serving as important negative gene regulators. In animals, miRNAs turn down protein translation by binding to the 3' UTR regions of target genes with imperfect complementary pairing. The identification of microRNA targets has become one of the major challenges of miRNA research. Bioinformatics investigations on miRNA target have resulted in a number of target prediction tools.
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CyTargetLinker
The high complexity and dynamic nature of the regulation of gene expression, protein synthesis, and protein activity pose a challenge to fully understand the cellular machinery. By deciphering the role of important players, including transcription factors, microRNAs, or small molecules, a better understanding of key regulatory processes can be obtained. Various databases contain information on the interactions of regulators with their targets for different organisms, data recently being extended with the results of the ENCODE (Encyclopedia of DNA Elements) project.
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miRvestigator
Transcriptome profiling studies have produced staggering numbers of gene co-expression signatures for a variety of biological systems. A significant fraction of these signatures will be partially or fully explained by miRNA-mediated targeted transcript degradation. miRvestigator takes as input lists of co-expressed genes from Caenorhabditis elegans, Drosophila melanogaster, G. gallus, Homo sapiens, Mus musculus or Rattus norvegicus and identifies the specific miRNAs that are likely to bind to 3' un-translated region (UTR) sequences to mediate the observed co-regulation.
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Lists2Networks
Systems biologists are faced with the difficulty of analyzing results from large-scale studies that profile the activity of many genes, RNAs and proteins, applied in different experiments, under different conditions, and reported in different publications. To address this challenge it is desirable to compare the results from different related studies such as mRNA expression microarrays, genome-wide ChIP-X, RNAi screens, proteomics and phosphoproteomics experiments in a coherent global framework.
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piRNA cluster database
Piwi proteins and their guiding small RNAs, termed Piwi-interacting (pi-) RNAs, are essential for silencing of transposons in the germline of animals. A substantial fraction of piRNAs originates from genomic loci termed piRNA clusters and sequences encoded in these piRNA clusters determine putative targets for the Piwi/piRNA system. In the past decade, studies of piRNA transcriptomes in different species revealed additional roles for piRNAs beyond transposon silencing, reflecting the astonishing plasticity of the Piwi/piRNA system along different phylogenetic branches.
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siRNAmod
Small interfering RNA (siRNA) technology has vast potential for functional genomics and development of therapeutics. However, it faces many obstacles predominantly instability of siRNAs due to nuclease digestion and subsequently biologically short half-life. Chemical modifications in siRNAs provide means to overcome these shortcomings and improve their stability and potency. Despite enormous utility bioinformatics resource of these chemically modified siRNAs (cm-siRNAs) is lacking.
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ZooMir
MicroRNAs (miRNAs) are endogenous non-protein-coding RNAs of approximately 22 nucleotides. Thousands of miRNA genes have been identified (computationally and/or experimentally) in a variety of organisms, which suggests that miRNA genes have been widely shared and distributed among species. Here, we used unique miRNA sequence patterns to scan the genome sequences of 56 bilaterian animal species for locating candidate miRNAs first.
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miRTarVis
MicroRNAs (miRNA) are short nucleotides that down-regulate its target genes. Various miRNA target prediction algorithms have used sequence complementarity between miRNA and its targets. Recently, other algorithms tried to improve sequence-based miRNA target prediction by exploiting miRNA-mRNA expression profile data. Some web-based tools are also introduced to help researchers predict targets of miRNAs from miRNA-mRNA expression profile data.
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