November 22, 2017 Conference paper Open Access

Craciun, Daniela; Sirugue, Jeremy; Montes, Matthieu

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{
  "description": "<p>We are currently developing a bio-shape similarity system for supplying high-throughput protein shape similarity applications within massive datasets. The proposed system is powered by a global-to-local shape similarity system which exploits shape elevation and local convexity attributes. In the first step, a global similarity is computed between the shape descriptors associated to each protein input. The procedure outputs best N similarities chosen by the user, within a query-to-cluster approach. The second stage is a patch-based local similarity computation method which is designed to find the best similar target from the cluster for supplying query-to-target protein retrieval applications. The local patch-based similarity comparison benefits of a multi-CPU implementation, offering thus fast query search capabilities within massive datasets. Experimental results on the SHREC 2017 BioShape dataset composed of 5484 models, illustrate the effectiveness of the proposed system.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Laboratoire GBA, EA4627, CNAM", 
      "@type": "Person", 
      "name": "Craciun, Daniela"
    }, 
    {
      "affiliation": "Laboratoire GBA, EA4627, CNAM", 
      "@type": "Person", 
      "name": "Sirugue, Jeremy"
    }, 
    {
      "affiliation": "Laboratoire GBA, EA4627, CNAM", 
      "@id": "https://orcid.org/0000-0001-5921-460X", 
      "@type": "Person", 
      "name": "Montes, Matthieu"
    }
  ], 
  "headline": "Global-to-local protein shape similarity system driven by digital elevation models", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2017-11-22", 
  "url": "https://zenodo.org/record/1167593", 
  "keywords": [
    "Shape similarity search, Protein structure, Computer vision"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1109/BIOSMART.2017.8095317", 
  "@id": "https://doi.org/10.1109/BIOSMART.2017.8095317", 
  "@type": "ScholarlyArticle", 
  "name": "Global-to-local protein shape similarity system driven by digital elevation models"
}