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  • Computational Methods, Genomics  (1)
  • drug accumulation  (1)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    European journal of clinical pharmacology 16 (1979), S. 331-334 
    ISSN: 1432-1041
    Keywords: netilmicin ; radioenzymatic assay ; drug accumulation ; pharmacokinetics
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology , Medicine
    Notes: Summary The pharmacokinetics of a single dose of netilmicin (NM) was studied in 6 healthy volunteers. Elimination of the drug was followed in serum and urine for 24 h and 72 h, respectively. NM concentrations were measured with a modified radioenzymatic assay. A three compartment open model was employed to calculate the pharmacokinetic parameters. Following the rapid initial distribution, biphasic elimination with half lives of 1.99 h (t1/2β) and 36.89 h (t1/2γ) was demonstrated. Measurable amounts of NM were excreted in the urine for up to 72 h. The volume of distribution at steady-state (Vdss) of 0.68 l/kg was 3 to 4 times larger than previously reported for this antibiotic. NM plasma clearance was 91 ml/min and the renal clearance was 67 ml/min. The data indicate that on repetitive dosing the amount of drug in the body would be considerably underestimated if the prolonged terminal elimination phase were not taken into account. During prolonged treatment, accumulation of NM in renal and other tissues is likely to occur, as has been described for other aminoglycosides. The possible consequences of this pharmacokinetic behaviour are discussed.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2016-05-20
    Description: Annotation of protein-coding genes is very important in bioinformatics and biology and has a decisive influence on many downstream analyses. Homology-based gene prediction programs allow for transferring knowledge about protein-coding genes from an annotated organism to an organism of interest. Here, we present a homology-based gene prediction program called GeMoMa. GeMoMa utilizes the conservation of intron positions within genes to predict related genes in other organisms. We assess the performance of GeMoMa and compare it with state-of-the-art competitors on plant and animal genomes using an extended best reciprocal hit approach. We find that GeMoMa often makes more precise predictions than its competitors yielding a substantially increased number of correct transcripts. Subsequently, we exemplarily validate GeMoMa predictions using Sanger sequencing. Finally, we use RNA-seq data to compare the predictions of homology-based gene prediction programs, and find again that GeMoMa performs well. Hence, we conclude that exploiting intron position conservation improves homology-based gene prediction, and we make GeMoMa freely available as command-line tool and Galaxy integration.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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