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  • 1
    Publication Date: 2014-11-21
    Description: We present detections at 850 μm of the Lyman-break galaxy (LBG) population at z   3, 4, and 5 using data from the Submillimetre Common User Bolometer Array 2 Cosmology Legacy Survey in the United Kingdom Infrared Deep Sky Survey ‘Ultra Deep Survey’ field. We employ stacking to probe beneath the survey limit, measuring the average 850 μm flux density of LBGs at z   3, 4, and 5 with typical ultraviolet luminosities of L 1700   10 29  erg s –1  Hz –1 . We measure 850 μm flux densities of (0.25 ± 0.03), (0.41 ± 0.06), and (0.88 ± 0.23) mJy, respectively, finding that they contribute at most 20 per cent to the cosmic far-infrared (IR) background at 850 μm. Fitting an appropriate range of spectral energy distributions to the z  ~ 3, 4, and 5 LBG stacked 24–850 μm fluxes, we derive IR luminosities of L 8-1000 μm 3.2, 5.5, and 11.0 10 11  L [and star formation rates (SFRs) of 50–200 M yr –1 ], respectively. We find that the evolution in the IR luminosity density of LBGs is broadly consistent with model predictions for the expected contribution of luminous-to-ultraluminous IR galaxies at these epochs. We observe a positive correlation between stellar mass and IR luminosity and confirm that, for a fixed mass, the reddest LBGs (UV slope β -〉 0) are redder due to dust extinction, with SFR(IR)/SFR(UV) increasing by about an order of magnitude over –2 〈 β 〈 0 with SFR(IR)/SFR(UV) ~ 20 for the reddest LBGs. Furthermore, the most massive LBGs tend to have higher obscured-to-unobscured ratios, hinting at a variation in the obscuration properties across the mass range.
    Print ISSN: 0035-8711
    Electronic ISSN: 1365-2966
    Topics: Physics
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  • 2
    Publication Date: 2016-12-23
    Description: Neonicotinoids are neurotoxic systemic insecticides used in plant protection worldwide. Unfortunately, application of neonicotinoids affects both beneficial and target insects indiscriminately. Being water soluble and persistent, these pesticides are capable of disrupting both food chains and biogeochemical cycles. This review focuses on the biodegradation of neonicotinoids in soil and water systems by the bacterial community. Several bacterial strains have been isolated and identified as capable of transforming neonicotinoids in the presence of an additional carbon source. Environmental parameters have been established for accelerated transformation in some of these strains. Studies have also indicated that enhanced biotransformation of these pesticides can be accomplished by mixed microbial populations under optimised environmental conditions. Substantial research into the identification of neonicotinoid-mineralising bacterial strains and identification of the genes and enzymes responsible for neonicotinoid degradation is still required to complete the understanding of microbial biodegradation pathways, and advance bioremediation efforts.
    Keywords: Environmental Microbiology
    Print ISSN: 0378-1097
    Electronic ISSN: 1574-6968
    Topics: Biology
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  • 3
    Publication Date: 2016-09-03
    Description: Although RNA-Seq data provide unprecedented isoform-level expression information, detection of alternative isoform regulation (AIR) remains difficult, particularly when working with an incomplete transcript annotation. We introduce JunctionSeq, a new method that builds on the statistical techniques used by the well-established DEXSeq package to detect differential usage of both exonic regions and splice junctions. In particular, JunctionSeq is capable of detecting differential usage of novel splice junctions without the need for an additional isoform assembly step, greatly improving performance when the available transcript annotation is flawed or incomplete. JunctionSeq also provides a powerful and streamlined visualization toolset that allows bioinformaticians to quickly and intuitively interpret their results. We tested our method on publicly available data from several experiments performed on the rat pineal gland and Toxoplasma gondii , successfully detecting known and previously validated AIR genes in 19 out of 19 gene-level hypothesis tests. Due to its ability to query novel splice sites, JunctionSeq is still able to detect these differences even when all alternative isoforms for these genes were not included in the transcript annotation. JunctionSeq thus provides a powerful method for detecting alternative isoform regulation even with low-quality annotations. An implementation of JunctionSeq is available as an R/Bioconductor package.
    Keywords: Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
    Publication Date: 2013-04-13
    Description: Motivation: Although several studies have used Bayesian classifiers for risk prediction using genome-wide single nucleotide polymorphism (SNP) datasets, no software can efficiently perform these analyses on massive genetic datasets and can accommodate multiple traits. Results: We describe the program PleioGRiP that performs a genome-wide Bayesian model search to identify SNPs associated with a discrete phenotype and uses SNPs ranked by Bayes factor to produce nested Bayesian classifiers. These classifiers can be used for genetic risk prediction, either selecting the classifier with optimal number of features or using an ensemble of classifiers. In addition, PleioGRiP implements an extension to the Bayesian search and classification and can search for pleiotropic relationships in which SNPs are simultaneosly associated with two or more distinct phenotypes. These relationships can be used to generate connected Bayesian classifiers to predict the phenotype of interest either using genetic data alone or in combination with the secondary phenotype(s). Availability: PleioGRiP is implemented in Java, and it is available from http://hdl.handle.net/2144/4367 . Contact: stephen.hartley@nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 5
    Publication Date: 2013-02-17
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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