Cell-type-specific signatures of microRNAs on target mRNA expression.

By Pranidhi Sood, A. Krek, Mihaela Zavolan, G. Macino, Nikolaus Rajewsky. Proceedings of the National Academy of Sciences of the United States of America, 2006

695 citations recorded by the source corpus.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c559e8d978b452fe28ed00335762a7885ae804c8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

1. Nikolaus Rajewsky
2. Scott M. Hammond
3. David P. Bartel
4. Eugene Berezikov
5. John S. Tsang
6. Alexander van Oudenaarden
7. Jun Zhu
8. Christopher Sander

In Molecular Biology

1. Nikolaus Rajewsky
2. Scott M. Hammond
3. David P. Bartel
4. Eugene Berezikov
5. Thomas Tuschl
6. Alexander van Oudenaarden
7. John S. Tsang
8. Jun Zhu

Citations in the corpus

• MicroRNAs in Common Human Diseases (2012, neutral): “Keywords: MicroRNA; Human diseases; Diagnostics; Therapeutics; Biomarker”
• Evolution of microRNA diversity and regulation in animals (2011, background): “Analyses of expression patterns of miRNAs and their predicted target genes have revealed two distinct trends in the expression of conserved and non-conserved targets relative to their cognate miRNA”
• Roles for microRNAs in conferring robustness to biological processes. (2012, neutral): “…analyses in fly, fish, and mouse have shown that miRNAs and their targets often have mutually exclusive RNA expression across tissues, especially in neighboring tissues derived from common progenitors (Farh et al., 2005; Stark et al., 2005; Sood et al., 2006; Tsang et al., 2007) (Figure 1).”
• Identification of miRNA Changes in Alzheimer's Disease Brain and CSF Yields Putative Biomarkers and Insights into Disease Pathways (2008, neutral): “Each gene with a sizeable 3’ UTR is capable of being regulated by multiple miRNAs and furthermore a single miRNA may bind multiple genes [59].”
• Mechanisms and consequences of alternative polyadenylation (2011, neutral): “In this case, low expression of the short isoform of BZW1 may be due to its unusually short 30 UTR, which is 25 times shorter than the average (500 nt) 30 UTR in testis germ cells (Sood et al., 2006) and may negatively affect translational efficiency (Tanguay and Gallie, 1996).”
• Detecting microRNA binding and siRNA off-target effects from expression data (2008, background): “Two previous studies3, 6 were aimed at this problem, but their methods are not available and fall short in ways of scalability, the ability to address composition biases, or the possibility of discovering an enrichment-based cut-off (Supplementary Discussion).”
• Transcriptome-wide analysis of regulatory interactions of the RNA-binding protein HuR. (2011, methodology): “We used the miReduce algorithm (Sood et al., 2006) to search for words in mRNA sequences associated with changes in perturbation experiments, finding UAUUUAU occurrence in 3'UTRs to be highly significantly associated with mRNA reduction upon HuR knock down (Suppl.”
• An overview of microRNAs (2015, background): “This can be done by microarray profiling and several analysis tools are available[112-115].”
• Dicer ablation affects antibody diversity and cell survival in the B lymphocyte lineage. (2008, positive): “Linear regression analysis was performed for all 16384 possible nucleotide motifs of length seven, as previously described (Bussemaker et al., 2001; Roven and Bussemaker, 2003; Sood et al., 2006 ).”
• microRNA target predictions in animals (2006, background): “The biological significance of this diversity remains to be evaluated, but because (i) 3′ UTR lengths of highly expressed genes are tissue dependen”
• MicroRNA expression alterations are linked to tumorigenesis and non-neoplastic processes in pancreatic ductal adenocarcinoma (2007, background): “…included also pancreatic tissue, but fall short in sample sizes and/or a systematic comparison of miRNA expression profiles between normal and PDAC tissues precluding the identification of PDAC-related miRNAs (Baskerville and Bartel, 2005; Lu et al., 2005; Sood et al., 2006; Volinia et al., 2006).”
• A mammalian microRNA expression atlas based on small RNA library sequencing. (2007, background): “Other mRNAs appear to be under selective pressure to avoid complementarity to coexpressed highly abundant miRNAs (Farh et al., 2005; Stark et al., 2005; Sood et al., 2006).”
• MicroRNA-mediated feedback and feedforward loops are recurrent network motifs in mammals. (2007, background): “, miR-133), where an increase in the miRNA level often coincides with a decrease in the levels of its target transcripts at the tissue level (Farh et al., 2005; Sood et al., 2006).”