Spontaneous bacterial peritonitis due to Arcanobacterium haemolyticum.
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Biomedical subjects
Publications and source records attributed to A D Farmer.
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In the past few decades, a wealth of genomic data has been produced in a wide variety of species using a diverse array of functional and molecular marker approaches. In order to unlock the full potential of the information contained in these independent experiments, researchers need efficient and intuitive means to identify common genomic regions and genes involved in the expression of target phenotypic traits across diverse conditions. To address this need, we have developed a Comparative Map and Trait Viewer (CMTV) tool that can be used to construct dynamic aggregations of a variety of types of genomic datasets. By algorithmically determining correspondences between sets of objects on multiple genomic maps, the CMTV can display syntenic regions across taxa, combine maps from separate experiments into a consensus map, or project data from different maps into a common coordinate framework using dynamic coordinate translations between source and target maps. We present a case study that illustrates the utility of the tool for managing large and varied datasets by integrating data collected by CIMMYT in maize drought tolerance research with data from public sources. This example will focus on one of the visualization features for Quantitative Trait Locus (QTL) data, using likelihood ratio (LR) files produced by generic QTL analysis software and displaying the data in a unique visual manner across different combinations of traits, environments and crosses. Once a genomic region of interest has been identified, the CMTV can search and display additional QTLs meeting a particular threshold for that region, or other functional data such as sets of differentially expressed genes located in the region; it thus provides an easily used means for organizing and manipulating data sets that have been dynamically integrated under the focus of the researcher's specific hypothesis.
The Medicago Genome Initiative (MGI) is a database of EST sequences of the model legume MEDICAGO: truncatula. The database is available to the public and has resulted from a collaborative research effort between the Samuel Roberts Noble Foundation and the National Center for Genome Resources to investigate the genome of M.truncatula. MGI is part of the greater integrated MEDICAGO: functional genomics program at the Noble Foundation (http://www.noble.org ), which is taking a global approach in studying the genetic and biochemical events associated with the growth, development and environmental interactions of this model legume. Our approach will include: large-scale EST sequencing, gene expression profiling, the generation of M.truncatula activation-tagged and promoter trap insertion mutants, high-throughput metabolic profiling, and proteome studies. These multidisciplinary information pools will be interfaced with one another to provide scientists with an integrated, holistic set of tools to address fundamental questions pertaining to legume biology. The public interface to the MGI database can be accessed at http://www.ncgr.org/research/mgi.
Power ultrasound may be used in the processing of minerals to clean their surfaces of oxidation products and fine coatings, mainly through the large, but very localised, forces produced by cavitation. Results of the application of power ultrasound to remove iron-rich coatings from the surfaces of silica sand used in glass making and to improve the electrostatic separation of mineral sand concentrates through lowering the resistivity of the conducting minerals (ilmenite and rutile) are presented. Parameters affecting ultrasonic cleaning, such as input power and levels of reagent addition, are discussed. In particular, we present data showing the relationship between power input and the particle size of surface coatings removed. This can be explained by the Derjaguin approximation for the energy of interaction between a sphere and a flat surface.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.