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Publications in SciGraph latest 20 shown

  • 2019-12 A blood-based signature of cerebrospinal fluid Aβ1–42 status in SCIENTIFIC REPORTS
  • 2018-12 Agent-based models of malaria transmission: a systematic review in MALARIA JOURNAL
  • 2018-12 A dual role for the N-terminal domain of the IL-3 receptor in cell signalling in NATURE COMMUNICATIONS
  • 2018-12 Agrochemicals increase risk of human schistosomiasis by supporting higher densities of intermediate hosts in NATURE COMMUNICATIONS
  • 2018-01-25 Hidden Storage in Data Centers: Gaining Flexibility Through Cooling Systems in MEASUREMENT, MODELLING AND EVALUATION OF COMPUTING SYSTEMS
  • 2018 Joint Registration And Segmentation Of Xray Images Using Generative Adversarial Networks in MACHINE LEARNING IN MEDICAL IMAGING
  • 2018 Deep Multiscale Convolutional Feature Learning for Weakly Supervised Localization of Chest Pathologies in X-ray Images in MACHINE LEARNING IN MEDICAL IMAGING
  • 2018 Efficient Active Learning for Image Classification and Segmentation Using a Sample Selection and Conditional Generative Adversarial Network in MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2018
  • 2018 Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images Using Bayesian Deep Learning in COMPUTATIONAL PATHOLOGY AND OPHTHALMIC MEDICAL IMAGE ANALYSIS
  • 2017-12 Mathematical model of TGF-βsignalling: feedback coupling is consistent with signal switching in BMC SYSTEMS BIOLOGY
  • 2017-10 Modelling apical columnar epithelium mechanics from circumferential contractile fibres in BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
  • 2017-08 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 in BMC NEUROSCIENCE
  • 2017 Image Super Resolution Using Generative Adversarial Networks and Local Saliency Maps for Retinal Image Analysis in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION − MICCAI 2017
  • 2016-08 25th Annual Computational Neuroscience Meeting: CNS-2016 in BMC NEUROSCIENCE
  • 2016 Sparse Coding Based Skin Lesion Segmentation Using Dynamic Rule-Based Refinement in MACHINE LEARNING IN MEDICAL IMAGING
  • 2015-12 High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies in HEALTH INFORMATION SCIENCE AND SYSTEMS
  • 2015-12 Gaining insight into cell wall cellulose macrofibril organisation by simulating microfibril adsorption in CELLULOSE
  • 2015-05 Regulating the Transport of DNA through Biofriendly Nanochannels in a Thin Solid Membrane in SCIENTIFIC REPORTS
  • 2015 Segmentation of Right Ventricle in Cardiac MR Images Using Shape Regression in MACHINE LEARNING IN MEDICAL IMAGING
  • 2015 Spatial Interpolation of Streaming Geosensor Network Data in the RISER System in WEB AND WIRELESS GEOGRAPHICAL INFORMATION SYSTEMS
  • JSON-LD is the canonical representation for SciGraph data.

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            "@value": "144.966914", 
            "type": "http://www.w3.org/2001/XMLSchema#float"
          }
        ], 
        "grid:cityName": [
          {
            "@value": "Melbourne"
          }
        ], 
        "grid:countryCode": [
          {
            "@value": "AU"
          }
        ], 
        "grid:countryName": [
          {
            "@value": "Australia"
          }
        ], 
        "grid:hasGeonamesCity": [
          {
            "id": "http://sws.geonames.org/2158177/"
          }
        ], 
        "id": "http://www.grid.ac/institutes/grid.481553.e/address-0", 
        "sdDataset": "grid", 
        "type": [
          "http://www.grid.ac/ontology/Address"
        ]
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://www.grid.ac/institutes/grid.481553.e'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://www.grid.ac/institutes/grid.481553.e'

    Turtle is a human-readable linked data format.

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    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://www.grid.ac/institutes/grid.481553.e'


     

    This table displays all metadata directly associated to this object as RDF triples.

    183 TRIPLES      11 PREDICATES      22 URIs      4 LITERALS

    Subject Predicate Object
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    3 grid:hasAddress grid-institutes:grid.481553.e/address-0
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    15 grid:hasWikidataId wd:Q19599437
    16 grid:id grid.481553.e
    17 grid:wikipediaPage https://en.wikipedia.org/wiki/IBM_Research_%E2%80%93_Australia
    18 rdf:type grid:Company
    19 foaf:Organization
    20 rdfs:label IBM Research - Australia
    21 skos:prefLabel IBM Research - Australia
    22 foaf:homepage http://research.ibm.com/labs/australia/index.shtml
    23 grid-institutes:grid.11447.37 sgo:sdDataset grid
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    35 foaf:homepage http://research.ibm.com/labs/haifa/index.shtml
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    80 grid:isni 0000 0004 0630 0661
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