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  • 548  (2)
  • Computational Methods, Massively Parallel (Deep) Sequencing, Genomics  (2)
  • International Union of Crystallography  (2)
  • Oxford University Press  (2)
  • American Institute of Physics
  • 1
    Publication Date: 2021-06-26
    Description: The high‐precision X‐ray diffraction setup for work with diamond anvil cells (DACs) in interaction chamber 2 (IC2) of the High Energy Density instrument of the European X‐ray Free‐Electron Laser is described. This includes beamline optics, sample positioning and detector systems located in the multipurpose vacuum chamber. Concepts for pump–probe X‐ray diffraction experiments in the DAC are described and their implementation demonstrated during the First User Community Assisted Commissioning experiment. X‐ray heating and diffraction of Bi under pressure, obtained using 20 fs X‐ray pulses at 17.8 keV and 2.2 MHz repetition, is illustrated through splitting of diffraction peaks, and interpreted employing finite element modeling of the sample chamber in the DAC.
    Description: The high‐precision X‐ray diffraction (XRD) setup for work with diamond anvil cells (DACs) in Interaction Chamber 2 of the High Energy Density (HED) instrument of the European X‐ray Free‐Electron Laser is described. image
    Keywords: 548 ; diamond anvil cells ; X‐ray free‐electron lasers ; high‐precision X‐ray diffraction ; finite element modeling
    Type: article
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  • 2
    Publication Date: 2021-03-27
    Description: A crystallographic indexing algorithm, pinkIndexer, is presented for the analysis of snapshot diffraction patterns. It can be used in a variety of contexts including measurements made with a monochromatic radiation source, a polychromatic source or with radiation of very short wavelength. As such, the algorithm is particularly suited to automated data processing for two emerging measurement techniques for macromolecular structure determination: serial pink‐beam X‐ray crystallography and serial electron crystallography, which until now lacked reliable programs for analyzing many individual diffraction patterns from crystals of uncorrelated orientation. The algorithm requires approximate knowledge of the unit‐cell parameters of the crystal, but not the wavelengths associated with each Bragg spot. The use of pinkIndexer is demonstrated by obtaining 1005 lattices from a published pink‐beam serial crystallography data set that had previously yielded 140 indexed lattices. Additionally, in tests on experimental serial crystallography diffraction data recorded with quasi‐monochromatic X‐rays and with electrons the algorithm indexed more patterns than other programs tested.
    Description: pinkIndexer, an algorithm developed for indexing of snapshot diffraction patterns recorded with pink‐beam X‐rays, monochromatic X‐rays and electrons, is described and its use evaluated. image
    Keywords: 548 ; indexing ; pinkIndexer ; CrystFEL ; pink X‐ray beam ; serial electron diffraction
    Type: article
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  • 3
    Publication Date: 2012-02-28
    Description: ChIP-seq is increasingly used to characterize transcription factor binding and chromatin marks at a genomic scale. Various tools are now available to extract binding motifs from peak data sets. However, most approaches are only available as command-line programs, or via a website but with size restrictions. We present peak-motifs , a computational pipeline that discovers motifs in peak sequences, compares them with databases, exports putative binding sites for visualization in the UCSC genome browser and generates an extensive report suited for both naive and expert users. It relies on time- and memory-efficient algorithms enabling the treatment of several thousand peaks within minutes. Regarding time efficiency, peak-motifs outperforms all comparable tools by several orders of magnitude. We demonstrate its accuracy by analyzing data sets ranging from 4000 to 1 28 000 peaks for 12 embryonic stem cell-specific transcription factors. In all cases, the program finds the expected motifs and returns additional motifs potentially bound by cofactors. We further apply peak-motifs to discover tissue-specific motifs in peak collections for the p300 transcriptional co-activator. To our knowledge, peak-motifs is the only tool that performs a complete motif analysis and offers a user-friendly web interface without any restriction on sequence size or number of peaks.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
    Publication Date: 2013-05-29
    Description: Deep transcriptome sequencing (RNA-Seq) has become a vital tool for studying the state of cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling data enable identification of novel isoforms, quantification of known isoforms and detection of changes in transcriptional or RNA-processing activity. Existing approaches to detect differential isoform abundance between samples either require a complete isoform annotation or fall short in providing statistically robust and calibrated significance estimates. Here, we propose a suite of statistical tests to address these open needs: a parametric test that uses known isoform annotations to detect changes in relative isoform abundance and a non-parametric test that detects differential read coverages and can be applied when isoform annotations are not available. Both methods account for the discrete nature of read counts and the inherent biological variability. We demonstrate that these tests compare favorably to previous methods, both in terms of accuracy and statistical calibrations. We use these techniques to analyze RNA-Seq libraries from Arabidopsis thaliana and Drosophila melanogaster. The identified differential RNA processing events were consistent with RT–qPCR measurements and previous studies. The proposed toolkit is available from http://bioweb.me/rdiff and enables in-depth analyses of transcriptomes, with or without available isoform annotation.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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