miRecords: an integrated resource for microRNA–target interactions

By Feifei Xiao, Zhixiang Zuo, G. Cai, Shuli Kang, Xiaolian Gao, Tongbin Li. Nucleic Acids Res., 2008

1,484 citations recorded by the source corpus.

MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2746310743557404f0ab73fafb78076761dccef5

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Citations in the corpus

MicroRNAs and complex diseases: from experimental results to computational models (2019, neutral): “com/miRecords/) [179] MiRecords is an integrated database, which includes 1135”
Identifying miRNAs, targets and functions (2012, background): “Several miRNA-target databases, such as TargetScan [36], PicTar [35], TarBase [74], miRecords [75] and miRWalk [76], store computationally predicted miRNA targets as well as few biologically validated ones.”
Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. (2013, methodology): “Various databases have been developed, using different algorithms to predict potential binding sites (Laganà et al., 2009; Xiao et al., 2009; Rieger et al., 2011).”
TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support (2011, background): “MiRecords (12) was first released in 2008.”
starBase: a database for exploring microRNA–mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data (2010, background): “In addition, several resources have been established to systematically collect and describe both experimentally validated miRNA targets [TarBase (13), miRecords (14)] and predicted miRNA targets [miRGator (15), MiRNAMap (16)].”
miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions (2013, background): “miRecords (22), an integrated resource for animal miRNA-target interaction, hosts a large, highquality manually curated database of experimentally validated miRNA-target interactions with systematic experimental documentation for each interaction.”
UTRdb and UTRsite (RELEASE 2010): a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs (2009, background): “UTRdb entries are also annotated for the occurrence of validated miRNA targets, collected in miRecords (16), a large, high-quality database of experimentally validated miRNA targets resulting from meticulous literature curation.”
deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks (2016, positive): “The creators of this repository obtained validated target sites from miRecords [49] database and mature human miRNA sequences from mirBase [15] database.”
DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA–gene interactions (2017, background): “miRecords (13) and miR2Disease (14) are smaller and not continuously updated repositories.”
miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets (2012, methodology): “Seven algorithms predicting miRNA targets, DIANA-microT [13,14], miRanda [9,22,23], mirBridge [15], PicTar [16], PITA [18] , rna22 [17] , and TargetScan [10,11,12], and two experimentally validated databases, TarBase [24] and miRecords [25], of miRNA target genes were included.”
miRBase: integrating microRNA annotation and deep-sequencing data (2010, background): “org (22)], together with lists of validated microRNA target sites [currently curated by resources such as TarBase (23), miRecords (24), miRTarBase].”
miRTarBase: a database curates experimentally validated microRNA–target interactions (2010, background): “…surveying pertinent literature (9). miRecords accumulates both experimentally validated miRNA targets and computationally predicted miRNA targets (10). miR2Disease contains relationships among miRNAs, target genes and diseases in humans (11). miRSel (12) incorporates a text-mining method to…”
miRWalk - Database: Prediction of possible miRNA binding sites by "walking" the genes of three genomes (2011, background): “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].”
PolymiRTS Database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways (2013, background): “We have collected >14 000 new experimentally supported miRNA–mRNA interactions from two recently updated databases, miRecords (35) and miRTarBase (36).”
miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database (2015, background): “…microRNA and disease associations and integrates miRNA-disease association data from genetics, epigenetics, circulating miRNAs and MTIs. miRecords (15) contains manually curated, experimentally validated and predicted miRNA targets from 11 established miRNA target prediction programs. miR2Disease…”