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MicroRNA targeting specificity in mammals: determinants beyond seed pairing.
TLDR
Five general features of site context that boost site efficacy are uncovered: AU-rich nucleotide composition near the site, proximity to sites for coexpressed miRNAs (which leads to cooperative action), proximity to residues pairing to miRNA nucleotides 13-16, positioning within the 3'UTR at least 15 nt from the stop codon, and positioning away from the center of long UTRs. Expand
Prediction of Plant MicroRNA Targets
TLDR
This work predicts regulatory targets for 14 Arabidopsis microRNAs (miRNAs) by identifying mRNAs with near complementarity and identifies members of transcription factor gene families involved in developmental patterning or cell differentiation. Expand
Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs
TLDR
These results suggest that metazoan miRNAs can reduce the levels of many of their target transcripts, not just the amount of protein deriving from these transcripts, and seem to downregulate a far greater number of targets than previously appreciated. Expand
An Abundant Class of Tiny RNAs with Probable Regulatory Roles in Caenorhabditis elegans
TLDR
Two small temporal RNAs, lin-4 andlet-7, control developmental timing in Caenorhabditis elegans and are found to be members of a large class of 21- to 24-nucleotide noncodingRNAs, called microRNAs (miRNAs), which imply that, as a class, miRNAs have broad regulatory functions in animals. Expand
The microRNAs of Caenorhabditis elegans.
TLDR
The census of the worm miRNAs and their expression patterns helps define this class of noncoding RNAs, lays the groundwork for functional studies, and provides the tools for more comprehensive analyses of miRNA genes in other species. Expand
A microRNA component of the p53 tumour suppressor network
TLDR
A family of miRNAs, miR-34a–c, whose expression reflected p53 status is described, whose encoded genes are direct transcriptional targets of p53, whose induction by DNA damage and oncogenic stress depends on p53 both in vitro and in vivo. Expand
Computational inference of homologous gene structures in the human genome.
TLDR
A new gene identification algorithm, GenomeScan, which combines exon-intron and splice signal models with similarity to known protein sequences in an integrated model, which shows an accurate and efficient automated approach for identifying genes in higher eukaryotic genomes and provide a first-level annotation of the draft human genome. Expand
Transcripts Targeted by the MicroRNA-16 Family Cooperatively Regulate Cell Cycle Progression
TLDR
It is demonstrated that a family of miRNAs sharing sequence identity with miRNA-16 (miR-16) negatively regulates cellular growth and cell cycle progression and coordinately regulates targets that may act in concert to controlcell cycle progression. Expand
Vertebrate MicroRNA Genes
TLDR
A computational procedure (MiRscan) is developed to identify miRNA genes and applies it here to miRNAs known to control the expression of other genes at the posttranscriptional level. Expand
Widespread siRNA "off-target" transcript silencing mediated by seed region sequence complementarity.
TLDR
In all cases, off-target transcript silencing was accompanied by loss of the corresponding protein and occurred with dependence on siRNA concentration similar to that of silencing of the target transcript. Expand
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