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  • 1
    Publication Date: 2013-01-17
    Description: Motivation: Systems Genetics approaches, in particular those relying on genetical genomics data, put forward a new paradigm of large-scale genome and network analysis. These methods use naturally occurring multi-factorial perturbations (e.g. polymorphisms) in properly controlled and screened genetic crosses to elucidate causal relationships in biological networks. However, although genetical genomics data contain rich information, a clear dissection of causes and effects as required for reconstructing gene regulatory networks is not easily possible. Results: We present a framework for reconstructing gene regulatory networks from genetical genomics data where genotype and phenotype correlation measures are used to derive an initial graph which is subsequently reduced by pruning strategies to minimize false positive predictions. Applied to realistic simulated genetic data from a recent DREAM challenge, we demonstrate that our approach is simple yet effective and outperforms more complex methods (including the best performer) with respect to (i) reconstruction quality (especially for small sample sizes) and (ii) applicability to large data sets due to relatively low computational costs. We also present reconstruction results from real genetical genomics data of yeast. Availability: A MATLAB implementation (script) of the reconstruction framework is available at www.mpi-magdeburg.mpg.de/projects/cna/etcdownloads.html Contact: klamt@mpi-magdeburg.mpg.de
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 2
    Publication Date: 2012-11-21
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 3
    Publication Date: 1993-08-01
    Print ISSN: 1053-4725
    Electronic ISSN: 1098-2256
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Wiley
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  • 4
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    Wiley
    In:  Environmental Toxicology & Water Quality, 8 (3). pp. 299-311.
    Publication Date: 2018-03-22
    Description: Current measures of microbe‐mediated biogeochemical processes in sediments were examined for their potential use as indicators of heavy metal ecotoxicity in both river sediments and bacterial cultures. Assays were carried out with HgCl2, CuSO4, and 3CdSO4 · 8H2O added to sediment samples and bacterial cell suspensions at concentrations ranging from 0.1 to 10 mM and 0.1 μM to 1 mM, respectively. Chemoautotrophic CO2 fixation by Elbe River sediment microbiota was most sensitive to Hg2+ and Cd2+, but not to Cu2+. Among the estimates of heterotrophic productivity, incorporation of leucine into cellular protein showed clearer dose responses than incorporation of thymidine into bacterial DNA. Thymidine incorporation was highly resistant to and even stimulated by metal ions, particularly in starved and anaerobic cultures of a test strain of Vibrio anguillarum. Similar metal ion induced “overshoot” responses beyond the levels of untreated controls were noted for mineralization of 14C‐glucose by V. anguillarum and, in the case of Cd2+, also in sediment. As a less complex measure of microbial respiratory activity, succinate dehydrogenase (SDH) showed normal dose responses without stimulatory effects, as long as bacterial cell homogenates were assayed. Despite this result, it is concluded that levels of SDH in natural sediment microbiota are inevitably affected by metal‐induced processes of selection and enzyme synthesis, and would thus fail to provide an appropriate measure of metal ecotoxicity. The final conclusion is that current parameters of microbial production and activity often reveal dose responses that do not fulfill basic requirements of ecotoxicity testing in metal‐polluted sediments.
    Type: Article , PeerReviewed
    Format: text
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