The organizers are happy to announce the upcoming “NGS and non-coding RNA data analysis” workshop II (2014) 15-16 May, Plovdiv, Bulgaria
The SeqAhead COST action BM1006 is organizing a 2 day workshop with presentations on non-coding RNA (ncRNA) research, bioinformatics, data analysis and stimulating discussions between biologists and bioinformaticians. The registration for this COST WS is now open.
The Workshop will concentrate on current topics in NGS and non-coding RNAs, with special emphasis on data analysis. The ultimate goal of the workshop is to bring software developers, bioinformaticians and experimental scientists together, bridging the gap between users’ needs and developers’ goals.
Workshop Target:
-biologists with research in ncRNA (ncRNA, small RNAs, miRNAs) applying or planning to apply Next Generation Sequencing technologies
-bioinformaticians involved in data analysis or developing algorithms for data analysis of ncRNA data.
The workshop is open for everybody in the ncRNA and NGS field. The workshop is free of charge and participants have to pay their own hotel and travel. COST will offer travel reimbursement to some selected researchers and you will need to provide a poster abstract.
For more detailed information visit the WS homepage:
For more specific information please contact Dr. Vesselin Baev {vebaev@plantgene.eu}
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Researchers at the University of Oxford and the Scripps Research Institute recently published an article evaluating the use of several different RT-qPCR normalization strategies when profiling miRNA gene expression in mouse serum. In their research article entitled “Assessment of RT-qPCR Normalization Strategies for Accurate Quantification of Extracellular microRNAs in Murine Serum,” Roberts et. al. compare three miRNA expression normalization strategies: 1.) normalization of miRNA expression to the average Cq (Ct) of all measured miRNA genes, 2.) Normalization of gene expression to individual miRNAs such as miR-16, miR-223, or miR-31 (all miRNA genes previously identified as normalization controls in the literature), and 3.) Normalization to a ‘spike-in’ external control miRNA gene expressed in C. elegans (cel-miR-39).
Normalization strategies have been an increasingly important topic in miRNA expression studies. This is especially true when profiling miRNA expression in serum or tissues and when quantifying miRNA genes which can have considerable variability in their endogenous expression. The authors identified a panel of 124 serum miRNA genes present in all their samples between normal, dystrophic, and dystrophic-treated mice. Their results suggest that [click to continue…]
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The goal of pharmacogenetics is to better understand human response to both environmental toxins and drug treatment. Recently, several laboratories have investigated the hypothesis that microRNA regulation of drug metabolizing enzymes may influence their expression and ultimately effect enzymatic activity and patient drug toxicities. Researchers at the Pennsylvania State Hershey College of Medicine and Washington State University, Spokane, identified miR-491-3p as a microRNA regulator of UDP-Glucuronosyltransferase (UGT) gene family members. In their article ‘Regulation of the UDP-Glucuronosyltransferase 1A1 Expression and Activity by MicroRNA 491-3p’, miR-491-3p is identified to target and bind with the common 3’ UTR of several UGT1A sub family gene members. Endogenous miR-491-3p expression in vitro had a significant impact on the gene expression of UGT1A1, UGT1A3, and UGT1A6 genes. miR-491-3p expression also effected UGT1A1 protein expression and metabolic activity against the substrate raloxifene, a chemotherapeutic drug used in the prevention and treatment of breast cancer.
Interestingly, Dluzen et. al. also observed inter-individual variable expression of miR-491-3p in human liver. Nearly one-third of the 39 liver samples analyzed lacked [click to continue…]
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StarBase has been updated to explore Pan-Cancer pattern of lncRNAs, miRNAs, RNA-binding proteins (RBP) and their regulatory networks (ceRNA, coexpression) by mining expression profiles of miRNAs, lncRNAs and mRNAs across 14 cancer types (>6000 samples) from The Cancer Genome Atlas (TCGA) Data Portal (all data available without limitations).- starBase constructed Pan-Cancer expression profiles of lncRNAs, miRNAs from TCGA RNA-Seq and miRNA-Seq data.
- starBase generated Pan-Cancer networks of CLIP-Seq experimentally supported miRNA-lncRNA and miRNA-mRNA interactions.
- starBase identified Pan-Cancer ceRNA networks involving lncRNAs and mRNAs by analyzing >6000 tumor and normal samples and [click to continue…]
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