The role of site accessibility in microRNA target recognition

By Michael Kertesz, Nicola Iovino, Ulrich Unnerstall, Ulrike Gaul, Eran Segal. Nature Genetics, 2007

1,686 citations recorded by the source corpus.

Subfields: Cancer Research, Immunology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/7299e65912bae10d46f711fa5e3ac16156eb12f6

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Citations in the corpus

miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions (2013, positive): “Many databases such as microRNA.org (10), miRGen (11), miRGator (12), miRDB (13) and miRNAMap (14) identify miRNA target interactions (MTIs) using a number of target prediction tools like TargetScan (15,16), miRanda (17), PicTar (18), RNAhybrid (19) and PITA (20).”
DIANA-microT web server: elucidating microRNA functions through target prediction (2009, positive): “Their specificity is usually increased by exploiting the commonly observed evolutionary conservation of the binding sites or by using additional features such as structural accessibility (4,5), nucleotide composition (6) as well as location of the binding sites within the 30-UTR (7).”
Hypoxia inducible mir-210 regulates normoxic gene expression involved in tumor initiation (2009, positive): “We then searched TargetScan, PicTar, mirRanda, and PITA programs compiling a list of 2754 potential mir-210 target genes (John et al., 2004; Kertesz et al., 2007; Krek et al., 2005; Lewis et al., 2005).”
Identifying miRNAs, targets and functions (2012, positive): “Another assessment was conducted by Alexiou et al. [51] who compared the performance for eight widely used target prediction programs, including EIMMo [52], miRanda [33], miRBase [53], PicTar [49], PITA [39], RNA22 [54] and TargetScan 5.0 [36], for the human and mouse genome, using experimentally va”
miR2Disease: a manually curated database for microRNA deregulation in human disease (2008, neutral): “target genes/sites of microRNAs, such as TargetScan (15), PicTar (16), RNAhybrid (17) and PITA (18).”
IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions (2008, positive): “For miRNAs and siRNAs, it was shown that the accessibility of the target sites has also an important influence (Shaoet al., 2007; Longet al., 2007; Amereset al., 2007; Kerteszet al., 2007; Kretschmer-Kazemi Far and Sczakiel, 2003; Luo and Chang, 2004).”
mirDIP 4.1—integrative database of human microRNA target predictions (2017, neutral): “PITA 2007 2008 yes yes (74) RAIN 2017 yes yes (15)”
miRmap: Comprehensive prediction of microRNA target repression strength (2012, neutral): “G total G Duplex+ G open Similar to G in PITA (12)”
Mapping the Human miRNA Interactome by CLASH Reveals Frequent Noncanonical Binding (2013, neutral): “CLASH targets were also compared to sets of miRNA targets bioinformatically predicted by the programs miRanda (John et al., 2004), PicTar (Krek et al., 2005), PITA (Kertesz et al., 2007), RNAhybrid (Rehmsmeier et al., 2004), and TargetScan (Lewis et al., 2005) (Table S4B).”
Desperately seeking microRNA targets (2010, neutral): “Other algorithms account for target site accessibilit”
MicroRNA-155 Is Regulated by the Transforming Growth Factor β/Smad Pathway and Contributes to Epithelial Cell Plasticity by Targeting RhoA (2008, neutral): “to be unpaired in a thermodynamically stable fashion (19).”
starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data (2013, neutral): “Genomic coordinates of these conserved miRNAs target sites predicted by TargetScan (25), miRanda/mirSVR (27), PITA (28), Pictar 2.0 (19) and RNA22 (29) were collected and converted to hg19, mm9/ mm10 and ce6/ce10 assemblies using LiftOver, respectively.”
The Immune Landscape of Cancer (2018, positive): “The second and third runs used PITA (Kertesz et al., 2007) and TargetScan (Agarwal et al., 2015) as input to the set-enrichment module to discover miRNA mediated regulation.”
miRecords: an integrated resource for microRNA–target interactions (2008, positive): “it was applied to study the importance of the 50 seed region for miRNA–target interactions (9), and of target accessibility features in assisting miRNA target discovery (26).”
miRWalk - Database: Prediction of possible miRNA binding sites by "walking" the genes of three genomes (2011, neutral): “In the past years, a large number of target prediction programs and databases on experimentally validated information have been developed for animal miRNAs [5,16–26].”