Search Results - (Author, Cooperation:E. Barr)

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  1. 1
    Bhandari S, Keane E, Barr E, et al.
    Oxford University Press
    Published 2018
    Staff View
    Publication Date:
    2018-03-06
    Publisher:
    Oxford University Press
    Print ISSN:
    0035-8711
    Electronic ISSN:
    1365-2966
    Topics:
    Physics
    Published by:
    http://global.oup.com/

    Latest Papers from Table of Contents or Articles in Press
  2. 2
    Staff View
    Publication Date:
    2018-04-19
    Publisher:
    American Physical Society (APS)
    Print ISSN:
    1098-0121
    Electronic ISSN:
    1095-3795
    Topics:
    Physics
    Keywords:
    Surface physics, nanoscale physics, low-dimensional systems
    Published by:
    http://www.aps.org/

    Latest Papers from Table of Contents or Articles in Press
  3. 3
    Staff View
    Publication Date:
    2018-02-08
    Publisher:
    Wiley-Blackwell
    Print ISSN:
    0007-1048
    Electronic ISSN:
    1365-2141
    Topics:
    Medicine
    Published by:
    http://www.wiley.com/wiley-blackwell

    Latest Papers from Table of Contents or Articles in Press
  4. 4
    Staff View
    Publication Date:
    2016-02-26
    Publisher:
    Nature Publishing Group (NPG)
    Print ISSN:
    0028-0836
    Electronic ISSN:
    1476-4687
    Topics:
    Biology
    Chemistry and Pharmacology
    Medicine
    Natural Sciences in General
    Physics
    Published by:
    http://www.nature.com/

    Latest Papers from Table of Contents or Articles in Press
  5. 5
    Leslie, S. W. ; Barr, E. ; Chandler, L. J.

    Oxford, UK : Blackwell Publishing Ltd
    Published 1983
    Staff View
    ISSN:
    1471-4159
    Source:
    Blackwell Publishing Journal Backfiles 1879-2005
    Topics:
    Medicine
    Notes:
    Abstract: 45Ca2+ uptake by synaptosomes isolated from cerebral cortex, cerebellum, midbrain, and brain stem of male Sprague-Dawley rats was measured at 1-, 3-, 5-, 15-, 30-, and 60-s time periods. The fastest rate of depolarization-dependent calcium uptake occurred in each brain region between 0 and 1 s. Uptake rates dropped off quickly with 3–5-s rates at approximately 15–20% of those observed at 0–1 s in cerebral cortex, cerebellum, and midbrain. Uptake rates at the 1–3-s interval were maintained at a relatively high rate in these three brain regions suggesting mixed fast- and slow-phase processes. The magnitude and rate of 45Ca2+ uptake were similar in synaptosomes from cerebral cortex, cerebellum, and midbrain but were significantly less in brain stem synaptosomes. These results suggest a fast and a slow component to voltage-dependent 45Ca2+ uptake by presynaptic nerve terminals from various brain regions.
    Type of Medium:
    Electronic Resource
    URL:
    http://dx.doi.org/10.1111/j.1471-4159.1983.tb00870.x

    Articles: DFG German National Licenses
  6. 6
    Swift, T. J. ; Barr, E. M.

    Oxford, UK : Blackwell Publishing Ltd
    Published 1973
    Staff View
    ISSN:
    1749-6632
    Source:
    Blackwell Publishing Journal Backfiles 1879-2005
    Topics:
    Natural Sciences in General
    Type of Medium:
    Electronic Resource
    URL:
    http://dx.doi.org/10.1111/j.1749-6632.1973.tb30779.x

    Articles: DFG German National Licenses
  7. 7
    Armstrong, R.D. ; Barr, E.

    Amsterdam : Elsevier
    Staff View
    ISSN:
    0368-1874
    Source:
    Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics:
    Chemistry and Pharmacology
    Type of Medium:
    Electronic Resource
    URL:
    http://linkinghub.elsevier.com/retrieve/pii/0368-1874(69)80062-6

    Articles: DFG German National Licenses
  8. 8
    Staff View
    ISSN:
    1573-4951
    Keywords:
    Automated prediction ; QSAR ; Molecular shape ; Ligand binding ; Molecular recognition
    Source:
    Springer Online Journal Archives 1860-2000
    Topics:
    Chemistry and Pharmacology
    Notes:
    Summary Building predictive models for iterative drug design in the absence of a known target protein structure is an important challenge. We present a novel technique, Compass, that removes a major obstacle to accurate prediction by automatically selecting conformations and alignments of molecules without the benefit of a characterized active site. The technique combines explicit representation of molecular shape with neural network learning methods to produce highly predictive models, even across chemically distinct classes of molecules. We apply the method to predicting human perception of musk odor and show how the resulting models can provide graphical guidance for chemical modifications.
    Type of Medium:
    Electronic Resource
    URL:
    http://dx.doi.org/10.1007/BF00124012

    Articles: DFG German National Licenses