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Publications (3)10.94 Total impact

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    ABSTRACT: ChIP-based technology is becoming the leading technology to globally profile thousands of transcription factors and elucidate the transcriptional regulation mechanisms in living cells. It has evolved rapidly in recent years, from hybridization with spotted or tiling microarray (ChIP-chip), to pair-end tag sequencing (ChIP-PET), to current massively parallel sequencing (ChIP-seq). Although there are many tools available for identifying binding sites (peaks) for ChIP-chip and ChIP-seq, few of them are available as easy-accessible online web tools for processing both ChIP-chip and ChIP-seq data for the ChIP-based user community. As such, we have developed a comprehensive web application tool for processing ChIP-chip and ChIP-seq data. Our web tool W-ChIPeaks employed a probe-based (or bin-based) enrichment threshold to define peaks and applied statistical methods to control false discovery rate for identified peaks. The web tool includes two different web interfaces: PELT for ChIP-chip, BELT for ChIP-seq, where both were tested on previously published experimental data. The novel features of our tool include a comprehensive output for identified peaks with GFF, BED, bedGraph and .wig formats, annotated genes to which these peaks are related, a graphical interpretation and visualization of the results via a user-friendly web interface. AVAILABILITY: http://motif.bmi.ohio-state.edu/W-ChIPeaks/.
    Bioinformatics 02/2011; 27(3):428-30. · 5.47 Impact Factor
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    ABSTRACT: W-ChIPMotifs is a web application tool that provides a user friendly interface for de novo motif discovery. The web tool is based on our previous ChIPMotifs program which is a de novo motif finding tool developed for ChIP-based high-throughput data and incorporated various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimized the significance of the detected motifs by using a bootstrap resampling statistic method and a Fisher test. Use of a randomized statistical model like bootstrap resampling can significantly increase the accuracy of the detected motifs. In our web tool, we have modified the program in two aspects: (i) we have refined the P-value with a Bonferroni correction; (ii) we have incorporated the STAMP tool to infer phylogenetic information and to determine the detected motifs if they are novel and known using the TRANSFAC and JASPAR databases. A comprehensive result file is mailed to users. Availability: http://motif.bmi.ohio-state.edu/ChIPMotifs. Data used in the article may be downloaded from http://motif.bmi.ohio-state.edu/ChIPMotifs/examples.shtml.
    Bioinformatics 10/2009; 25(23):3191-3. · 5.47 Impact Factor
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    ABSTRACT: W-ChIPMotifs is a web application tool that provides a user friendly interface for de novo motif discovery. The web tool is based on our previous ChIPMotifs program which is a de novo motif finding tool developed for ChIP-based high-throughput data and incorporated various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimized the significance of the detected motifs by using a bootstrap resampling statistic method and a Fisher test. Use of a randomized statistical model like bootstrap resampling can significantly increase the accuracy of the detected motifs. In our web tool, we have modified the program in two aspects: (i) we have refined the P-value with a Bonferroni correction; (ii) we have incorporated the STAMP tool to infer phylogenetic information and to determine the detected motifs if they are novel and known using the TRANSFAC and JASPAR databases. A comprehensive result file is mailed to users.
    Bioinformatics. 01/2009; 25:3191-3193.