Search Results - "Burgess, Karl"

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  1. 1

    Topic modeling for untargeted substructure exploration in metabolomics by van der Hooft, Justin Johan Jozias, Wandy, Joe, Barrett, Michael P., Burgess, Karl E. V., Rogers, Simon

    “…The potential of untargeted metabolomics to answer important questions across the life sciences is hindered because of a paucity of computational tools that…”
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  2. 2

    Toward Global Metabolomics Analysis with Hydrophilic Interaction Liquid Chromatography–Mass Spectrometry: Improved Metabolite Identification by Retention Time Prediction by Creek, Darren J, Jankevics, Andris, Breitling, Rainer, Watson, David G, Barrett, Michael P, Burgess, Karl E. V

    Published in Analytical chemistry (Washington) (15-11-2011)
    “…Metabolomics is an emerging field of postgenomic biology concerned with comprehensive analysis of small molecules in biological systems. However, difficulties…”
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  3. 3

    IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data by CREEK, Darren J, JANKEVICS, Andris, BURGESS, Karl E. V, BREITLING, Rainer, BARRETT, Michael P

    Published in Bioinformatics (Oxford, England) (01-04-2012)
    “…The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data…”
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  4. 4

    Stable Isotope-Assisted Metabolomics for Network-Wide Metabolic Pathway Elucidation by Creek, Darren J, Chokkathukalam, Achuthanunni, Jankevics, Andris, Burgess, Karl E. V, Breitling, Rainer, Barrett, Michael P

    Published in Analytical chemistry (Washington) (16-10-2012)
    “…The combination of high-resolution LC–MS-based untargeted metabolomics with stable isotope tracing provides a global overview of the cellular fate of precursor…”
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    Nacre Topography Produces Higher Crystallinity in Bone than Chemically Induced Osteogenesis by Alakpa, Enateri V, Burgess, Karl E. V, Chung, Peter, Riehle, Mathis O, Gadegaard, Nikolaj, Dalby, Matthew John, Cusack, Maggie

    Published in ACS nano (25-07-2017)
    “…It is counterintuitive that invertebrate shells can induce bone formation, yet nacre, or mother of pearl, from marine shells is both osteoinductive and…”
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  7. 7

    Unsupervised Discovery and Comparison of Structural Families Across Multiple Samples in Untargeted Metabolomics by van der Hooft, Justin J. J, Wandy, Joe, Young, Francesca, Padmanabhan, Sandosh, Gerasimidis, Konstantinos, Burgess, Karl E. V, Barrett, Michael P, Rogers, Simon

    Published in Analytical chemistry (Washington) (18-07-2017)
    “…In untargeted metabolomics approaches, the inability to structurally annotate relevant features and map them to biochemical pathways is hampering the full…”
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    Skeletal stem cell physiology on functionally distinct titania nanotopographies by McNamara, Laura E, Sjöström, Terje, Burgess, Karl E.V, Kim, Joseph J.W, Liu, Er, Gordonov, Simon, Moghe, Prabhas V, Meek, R.M. Dominic, Oreffo, Richard O.C, Su, Bo, Dalby, Matthew J

    Published in Biomaterials (01-10-2011)
    “…Abstract Functionalisation of the surface of orthopaedic implants with nanotopographies that could stimulate in situ osteogenic differentiation of the…”
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  10. 10

    Nanoscale surfaces for the long-term maintenance of mesenchymal stem cell phenotype and multipotency by McMurray, Rebecca J., Gadegaard, Nikolaj, Tsimbouri, P. Monica, Burgess, Karl V., McNamara, Laura E., Tare, Rahul, Murawski, Kate, Kingham, Emmajayne, Oreffo, Richard O. C., Dalby, Matthew J.

    Published in Nature materials (17-07-2011)
    “…There is currently an unmet need for the supply of autologous, patient-specific stem cells for regenerative therapies in the clinic. Mesenchymal stem cell…”
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    A novel metabolomic approach used for the comparison of Staphylococcus aureus planktonic cells and biofilm samples by Stipetic, Laurence H., Dalby, Matthew J., Davies, Robert L., Morton, Fraser R., Ramage, Gordon, Burgess, Karl E. V.

    Published in Metabolomics (01-04-2016)
    “…Introduction Bacterial cell characteristics change significantly during differentiation between planktonic and biofilm states. While established methods exist…”
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  12. 12

    The emergence of proton nuclear magnetic resonance metabolomics in the cardiovascular arena as viewed from a clinical perspective by Rankin, Naomi J, Preiss, David, Welsh, Paul, Burgess, Karl E.V, Nelson, Scott M, Lawlor, Debbie A, Sattar, Naveed

    Published in Atherosclerosis (01-11-2014)
    “…Abstract The ability to phenotype metabolic profiles in serum has increased substantially in recent years with the advent of metabolomics. Metabolomics is the…”
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  13. 13

    MetAssign: probabilistic annotation of metabolites from LC-MS data using a Bayesian clustering approach by Daly, Rónán, Rogers, Simon, Wandy, Joe, Jankevics, Andris, Burgess, Karl E V, Breitling, Rainer

    Published in Bioinformatics (Oxford, England) (01-10-2014)
    “…The use of liquid chromatography coupled to mass spectrometry has enabled the high-throughput profiling of the metabolite composition of biological samples…”
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  14. 14

    Substantial Extracellular Metabolic Differences Found Between Phylogenetically Closely Related Probiotic and Pathogenic Strains of Escherichia coli by van der Hooft, Justin J J, Goldstone, Robert J, Harris, Susan, Burgess, Karl E V, Smith, David G E

    Published in Frontiers in microbiology (2019)
    “…Since its first isolation a century ago, the gut inhabitant strain Nissle 1917 has been shown to have probiotic activities; however, it is yet not fully…”
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  15. 15

    Nanotopographical Induction of Osteogenesis through Adhesion, Bone Morphogenic Protein Cosignaling, and Regulation of MicroRNAs by Yang, Jingli, McNamara, Laura E, Gadegaard, Nikolaj, Alakpa, Enateri V, Burgess, Karl V, Meek, R. M. Dominic, Dalby, Matthew J

    Published in ACS nano (28-10-2014)
    “…It is emerging that nanotopographical information can be used to induce osteogenesis from mesenchymal stromal cells from the bone marrow, and it is hoped that…”
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  16. 16

    Candida albicans Mycofilms Support Staphylococcus aureus Colonization and Enhances Miconazole Resistance in Dual-Species Interactions by Kean, Ryan, Rajendran, Ranjith, Haggarty, Jennifer, Townsend, Eleanor M, Short, Bryn, Burgess, Karl E, Lang, Sue, Millington, Owain, Mackay, William G, Williams, Craig, Ramage, Gordon

    Published in Frontiers in microbiology (23-02-2017)
    “…Polymicrobial inter-kingdom biofilm infections represent a clinical management conundrum. The presence of co-isolation of bacteria and fungi complicates the…”
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  17. 17

    Biostimulants for Plant Growth and Mitigation of Abiotic Stresses: A Metabolomics Perspective by Nephali, Lerato, Piater, Lizelle A, Dubery, Ian A, Patterson, Veronica, Huyser, Johan, Burgess, Karl, Tugizimana, Fidele

    Published in Metabolites (10-12-2020)
    “…Adverse environmental conditions due to climate change, combined with declining soil fertility, threaten food security. Modern agriculture is facing a pressing…”
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  18. 18

    A novel targeted/untargeted GC-Orbitrap metabolomics methodology applied to Candida albicans and Staphylococcus aureus biofilms by Weidt, Stefan, Haggarty, Jennifer, Kean, Ryan, Cojocariu, Cristian I., Silcock, Paul J., Rajendran, Ranjith, Ramage, Gordon, Burgess, Karl E. V.

    Published in Metabolomics (01-12-2016)
    “…Introduction Combined infections from Candida albicans and Staphylococcus aureus are a leading cause of death in the developed world. Evidence suggests that…”
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    Dynamic Surfaces for the Study of Mesenchymal Stem Cell Growth through Adhesion Regulation by Roberts, Jemma N, Sahoo, Jugal Kishore, McNamara, Laura E, Burgess, Karl V, Yang, Jingli, Alakpa, Enateri V, Anderson, Hilary J, Hay, Jake, Turner, Lesley-Anne, Yarwood, Stephen J, Zelzer, Mischa, Oreffo, Richard O. C, Ulijn, Rein V, Dalby, Matthew J

    Published in ACS nano (26-07-2016)
    “…Out of their niche environment, adult stem cells, such as mesenchymal stem cells (MSCs), spontaneously differentiate. This makes both studying these important…”
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  20. 20

    Optimisation of surfactin yield in Bacillus using data-efficient active learning and high-throughput mass spectrometry by Albornoz, Ricardo Valencia, Oyarzún, Diego, Burgess, Karl

    “…Integration of machine learning and high throughput measurements are essential to drive the next generation of the design-build-test-learn (DBTL) cycle in…”
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