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Articles by I Birol
Total Records ( 2 ) for I Birol
  M Krzywinski , J Schein , I Birol , J Connors , R Gascoyne , D Horsman , S. J Jones and M. A. Marra
 

We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals. Such data are routinely produced by sequence alignments, hybridization arrays, genome mapping, and genotyping studies. Circos uses a circular ideogram layout to facilitate the display of relationships between pairs of positions by the use of ribbons, which encode the position, size, and orientation of related genomic elements. Circos is capable of displaying data as scatter, line, and histogram plots, heat maps, tiles, connectors, and text. Bitmap or vector images can be created from GFF-style data inputs and hierarchical configuration files, which can be easily generated by automated tools, making Circos suitable for rapid deployment in data analysis and reporting pipelines.

  B. G Hoffman , G Robertson , B Zavaglia , M Beach , R Cullum , S Lee , G Soukhatcheva , L Li , E. D Wederell , N Thiessen , M Bilenky , T Cezard , A Tam , B Kamoh , I Birol , D Dai , Y Zhao , M Hirst , C. B Verchere , C. D Helgason , M. A Marra , S. J. M Jones and P. A. Hoodless
 

The liver and pancreas share a common origin and coexpress several transcription factors. To gain insight into the transcriptional networks regulating the function of these tissues, we globally identify binding sites for FOXA2 in adult mouse islets and liver, PDX1 in islets, and HNF4A in liver. Because most eukaryotic transcription factors bind thousands of loci, many of which are thought to be inactive, methods that can discriminate functionally active binding events are essential for the interpretation of genome-wide transcription factor binding data. To develop such a method, we also generated genome-wide H3K4me1 and H3K4me3 localization data in these tissues. By analyzing our binding and histone methylation data in combination with comprehensive gene expression data, we show that H3K4me1 enrichment profiles discriminate transcription factor occupied loci into three classes: those that are functionally active, those that are poised for activation, and those that reflect pioneer-like transcription factor activity. Furthermore, we demonstrate that the regulated presence of H3K4me1-marked nucleosomes at transcription factor occupied promoters and enhancers controls their activity, implicating both tissue-specific transcription factor binding and nucleosome remodeling complex recruitment in determining tissue-specific gene expression. Finally, we apply these approaches to generate novel insights into how FOXA2, PDX1, and HNF4A cooperate to drive islet- and liver-specific gene expression.

 
 
 
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