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  • Artikel  (3)
  • Computational Methods, Ribosomes and Protein Translation, Massively Parallel (Deep) Sequencing, Genomics, Transcriptome Mapping - Monitoring Gene Expression  (1)
  • Nucleic acid structure, RNA characterisation and manipulation, Computational Methods  (1)
  • Professional Development  (1)
  • Oxford University Press  (3)
  • 2015-2019  (3)
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  • Artikel  (3)
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  • Oxford University Press  (3)
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  • 2015-2019  (3)
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  • 1
    Publikationsdatum: 2016-06-15
    Beschreibung: In the yearly Internationally Genetically Engineered Machines (iGEM) competition, teams of Bachelor's and Master's students design and build an engineered biological system using DNA technologies. Advising an iGEM team poses unique challenges due to the inherent difficulties of mounting and completing a new biological project from scratch over the course of a single academic year; the challenges in obtaining financial and structural resources for a project that will likely not be fully realized; and conflicts between educational and competition-based goals. This article shares tips and best practices for iGEM team advisors, from two team advisors with very different experiences with the iGEM competition.
    Schlagwort(e): Professional Development
    Print ISSN: 0378-1097
    Digitale ISSN: 1574-6968
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    Publikationsdatum: 2015-03-14
    Beschreibung: An increasing amount of studies integrate mRNA sequencing data into MS-based proteomics to complement the translation product search space. However, several factors, including extensive regulation of mRNA translation and the need for three- or six-frame-translation, impede the use of mRNA-seq data for the construction of a protein sequence search database. With that in mind, we developed the PROTEOFORMER tool that automatically processes data of the recently developed ribosome profiling method (sequencing of ribosome-protected mRNA fragments), resulting in genome-wide visualization of ribosome occupancy. Our tool also includes a translation initiation site calling algorithm allowing the delineation of the open reading frames (ORFs) of all translation products. A complete protein synthesis-based sequence database can thus be compiled for mass spectrometry-based identification. This approach increases the overall protein identification rates with 3% and 11% (improved and new identifications) for human and mouse, respectively, and enables proteome-wide detection of 5'-extended proteoforms, upstream ORF translation and near-cognate translation start sites. The PROTEOFORMER tool is available as a stand-alone pipeline and has been implemented in the galaxy framework for ease of use.
    Schlagwort(e): Computational Methods, Ribosomes and Protein Translation, Massively Parallel (Deep) Sequencing, Genomics, Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 3
    Publikationsdatum: 2016-04-21
    Beschreibung: RNA–RNA interactions are fast emerging as a major functional component in many newly discovered non-coding RNAs. Basepairing is believed to be a major contributor to the stability of these intermolecular interactions, much like intramolecular basepairs formed in RNA secondary structure. As such, using algorithms similar to those for predicting RNA secondary structure, computational methods have been recently developed for the prediction of RNA–RNA interactions. We provide the first comprehensive comparison comprising 14 methods that predict general intermolecular basepairs. To evaluate these, we compile an extensive data set of 54 experimentally confirmed fungal snoRNA–rRNA interactions and 102 bacterial sRNA–mRNA interactions. We test the performance accuracy of all methods, evaluating the effects of tool settings, sequence length, and multiple sequence alignment usage and quality. Our results show that—unlike for RNA secondary structure prediction—the overall best performing tools are non-comparative energy-based tools utilizing accessibility information that predict short interactions on this data set. Furthermore, we find that maintaining high accuracy across biologically different data sets and increasing input lengths remains a huge challenge, causing implications for de novo transcriptome-wide searches. Finally, we make our interaction data set publicly available for future development and benchmarking efforts.
    Schlagwort(e): Nucleic acid structure, RNA characterisation and manipulation, Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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