Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2013-04

AUTHORS

Daniel Eisinger, George Tsatsaronis, Markus Bundschus, Ulrich Wieneke, Michael Schroeder

ABSTRACT

Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms.Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources. More... »

PAGES

s3

References to SciGraph publications

  • 2003-12. Information extraction from full text scientific articles: Where are the keywords? in BMC BIOINFORMATICS
  • 2009-02. Evaluation of query expansion using MeSH in PubMed in INFORMATION RETRIEVAL JOURNAL
  • 2010. Patent Retrieval Experiments in the Context of the CLEF IP Track 2009 in MULTILINGUAL INFORMATION ACCESS EVALUATION I. TEXT RETRIEVAL EXPERIMENTS
  • 2010. Prior Art Search Using International Patent Classification Codes and All-Claims-Queries in MULTILINGUAL INFORMATION ACCESS EVALUATION I. TEXT RETRIEVAL EXPERIMENTS
  • 2011. Introduction to Patent Searching in CURRENT CHALLENGES IN PATENT INFORMATION RETRIEVAL
  • 2012-12. A Maximum-Entropy approach for accurate document annotation in the biomedical domain in JOURNAL OF BIOMEDICAL SEMANTICS
  • 2013-02. Analysing patent landscapes in plant biotechnology and new plant breeding techniques in TRANSGENIC RESEARCH
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/2041-1480-4-s1-s3

    DOI

    http://dx.doi.org/10.1186/2041-1480-4-s1-s3

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1020021502

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/23734562


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information Systems", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Roche (Germany)", 
              "id": "https://www.grid.ac/institutes/grid.424277.0", 
              "name": [
                "TU Dresden, BIOTEC, Tatzberg 47/49, 01307, Dresden, Germany", 
                "Roche Diagnostics GmbH, Nonnenwald 2, 82377, Penzberg, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Eisinger", 
            "givenName": "Daniel", 
            "id": "sg:person.015666015012.74", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015666015012.74"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "TU Dresden", 
              "id": "https://www.grid.ac/institutes/grid.4488.0", 
              "name": [
                "TU Dresden, BIOTEC, Tatzberg 47/49, 01307, Dresden, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tsatsaronis", 
            "givenName": "George", 
            "id": "sg:person.014720756671.61", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014720756671.61"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Roche (Germany)", 
              "id": "https://www.grid.ac/institutes/grid.424277.0", 
              "name": [
                "Roche Diagnostics GmbH, Nonnenwald 2, 82377, Penzberg, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Bundschus", 
            "givenName": "Markus", 
            "id": "sg:person.0766734503.51", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0766734503.51"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Roche (Germany)", 
              "id": "https://www.grid.ac/institutes/grid.424277.0", 
              "name": [
                "Roche Diagnostics GmbH, Nonnenwald 2, 82377, Penzberg, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wieneke", 
            "givenName": "Ulrich", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "TU Dresden", 
              "id": "https://www.grid.ac/institutes/grid.4488.0", 
              "name": [
                "TU Dresden, BIOTEC, Tatzberg 47/49, 01307, Dresden, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Schroeder", 
            "givenName": "Michael", 
            "id": "sg:person.01127320076.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01127320076.40"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1002/hbm.22268", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001637414"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2147/ott.s43122", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002094397"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.wpi.2004.01.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002623207"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10791-008-9074-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007640210", 
              "https://doi.org/10.1007/s10791-008-9074-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp249", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009025850"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0172-2190(90)90285-s", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009344425"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2041-1480-3-s1-s2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012075462", 
              "https://doi.org/10.1186/2041-1480-3-s1-s2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.wpi.2011.09.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012640331"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1136/jamia.2001.0080317", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013384230"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.wpi.2012.03.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014712620"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1871888.1871894", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020330246"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11248-012-9641-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021549882", 
              "https://doi.org/10.1007/s11248-012-9641-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/945546.945547", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022313315"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15754-7_59", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022361915", 
              "https://doi.org/10.1007/978-3-642-15754-7_59"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0172-2190(02)00026-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022771847"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2006.01.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023011065"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.wpi.2012.01.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026461049"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15754-7_54", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027780665", 
              "https://doi.org/10.1007/978-3-642-15754-7_54"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-15754-7_54", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027780665", 
              "https://doi.org/10.1007/978-3-642-15754-7_54"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btl302", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029305588"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/csla.1996.0011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029750983"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-4-20", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033906699", 
              "https://doi.org/10.1186/1471-2105-4-20"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3169/itej1978.34.58", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038443433"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-19231-9_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039616907", 
              "https://doi.org/10.1007/978-3-642-19231-9_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-19231-9_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039616907", 
              "https://doi.org/10.1007/978-3-642-19231-9_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bth291", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041160894"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0172-2190(00)00110-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043026371"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btm557", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043760998"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0172-2190(00)00073-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048824208"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5260/chara.13.1.32", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051272970"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gki470", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051996212"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ipm.2011.11.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052831817"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.12927/cjnl.2012.22807", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064751877"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3163/1536-5050.100.3.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1071062791"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4018/978-1-59904-373-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1096031746"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4018/978-1-59904-373-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1096031746"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2013-04", 
        "datePublishedReg": "2013-04-01", 
        "description": "Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms.Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/2041-1480-4-s1-s3", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1043573", 
            "issn": [
              "2041-1480"
            ], 
            "name": "Journal of Biomedical Semantics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "Suppl 1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "4"
          }
        ], 
        "name": "Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed", 
        "pagination": "s3", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "5f64f97dcbf76fbe197a839b4010978c2221ea39a944531861b935a20104f2c1"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "23734562"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101531992"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/2041-1480-4-s1-s3"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1020021502"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/2041-1480-4-s1-s3", 
          "https://app.dimensions.ai/details/publication/pub.1020021502"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T18:25", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8675_00000536.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1186%2F2041-1480-4-S1-S3"
      }
    ]
     

    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://scigraph.springernature.com/pub.10.1186/2041-1480-4-s1-s3'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/2041-1480-4-s1-s3'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/2041-1480-4-s1-s3'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/2041-1480-4-s1-s3'


     

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

    205 TRIPLES      21 PREDICATES      62 URIs      21 LITERALS      9 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/2041-1480-4-s1-s3 schema:about anzsrc-for:08
    2 anzsrc-for:0806
    3 schema:author Ne80a9971120045d2af02ab6c63db8d91
    4 schema:citation sg:pub.10.1007/978-3-642-15754-7_54
    5 sg:pub.10.1007/978-3-642-15754-7_59
    6 sg:pub.10.1007/978-3-642-19231-9_1
    7 sg:pub.10.1007/s10791-008-9074-8
    8 sg:pub.10.1007/s11248-012-9641-z
    9 sg:pub.10.1186/1471-2105-4-20
    10 sg:pub.10.1186/2041-1480-3-s1-s2
    11 https://doi.org/10.1002/hbm.22268
    12 https://doi.org/10.1006/csla.1996.0011
    13 https://doi.org/10.1016/0172-2190(90)90285-s
    14 https://doi.org/10.1016/j.eswa.2006.01.013
    15 https://doi.org/10.1016/j.ipm.2011.11.001
    16 https://doi.org/10.1016/j.wpi.2004.01.003
    17 https://doi.org/10.1016/j.wpi.2011.09.003
    18 https://doi.org/10.1016/j.wpi.2012.01.007
    19 https://doi.org/10.1016/j.wpi.2012.03.003
    20 https://doi.org/10.1016/s0172-2190(00)00073-9
    21 https://doi.org/10.1016/s0172-2190(00)00110-1
    22 https://doi.org/10.1016/s0172-2190(02)00026-1
    23 https://doi.org/10.1093/bioinformatics/bth291
    24 https://doi.org/10.1093/bioinformatics/btl302
    25 https://doi.org/10.1093/bioinformatics/btm557
    26 https://doi.org/10.1093/bioinformatics/btp249
    27 https://doi.org/10.1093/nar/gki470
    28 https://doi.org/10.1136/jamia.2001.0080317
    29 https://doi.org/10.1145/1871888.1871894
    30 https://doi.org/10.1145/945546.945547
    31 https://doi.org/10.12927/cjnl.2012.22807
    32 https://doi.org/10.2147/ott.s43122
    33 https://doi.org/10.3163/1536-5050.100.3.007
    34 https://doi.org/10.3169/itej1978.34.58
    35 https://doi.org/10.4018/978-1-59904-373-9
    36 https://doi.org/10.5260/chara.13.1.32
    37 schema:datePublished 2013-04
    38 schema:datePublishedReg 2013-04-01
    39 schema:description Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms.Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources.
    40 schema:genre research_article
    41 schema:inLanguage en
    42 schema:isAccessibleForFree true
    43 schema:isPartOf N75a1b146110643b782b9b74e3a8e30c5
    44 Nb214803478ab45caad6c5912f371692d
    45 sg:journal.1043573
    46 schema:name Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed
    47 schema:pagination s3
    48 schema:productId N1a60fd61038d432c89a5e1ad4cc90777
    49 N2fa78283bdb643b5a976416a97d4cd31
    50 N3c183279f964476f80a8e3c5f5a31061
    51 Na1516ffa12304950aecf7a4aa5747a25
    52 Nde86785dabda42548c64c8d52fb46076
    53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020021502
    54 https://doi.org/10.1186/2041-1480-4-s1-s3
    55 schema:sdDatePublished 2019-04-10T18:25
    56 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    57 schema:sdPublisher N37893ea6bea44a408bd1f49456588e7d
    58 schema:url http://link.springer.com/10.1186%2F2041-1480-4-S1-S3
    59 sgo:license sg:explorer/license/
    60 sgo:sdDataset articles
    61 rdf:type schema:ScholarlyArticle
    62 N19ea98e9e5a74830a9b32a4d0ea5b67c rdf:first sg:person.01127320076.40
    63 rdf:rest rdf:nil
    64 N1a60fd61038d432c89a5e1ad4cc90777 schema:name doi
    65 schema:value 10.1186/2041-1480-4-s1-s3
    66 rdf:type schema:PropertyValue
    67 N2fa78283bdb643b5a976416a97d4cd31 schema:name readcube_id
    68 schema:value 5f64f97dcbf76fbe197a839b4010978c2221ea39a944531861b935a20104f2c1
    69 rdf:type schema:PropertyValue
    70 N37893ea6bea44a408bd1f49456588e7d schema:name Springer Nature - SN SciGraph project
    71 rdf:type schema:Organization
    72 N3c183279f964476f80a8e3c5f5a31061 schema:name dimensions_id
    73 schema:value pub.1020021502
    74 rdf:type schema:PropertyValue
    75 N542ef4eeba404b49bdc85b49aaf9cc86 rdf:first N9e001a66ba0b4a849d3b6c1d852631ec
    76 rdf:rest N19ea98e9e5a74830a9b32a4d0ea5b67c
    77 N6265f2aad5984700aa9e31d8e7f0c294 rdf:first sg:person.014720756671.61
    78 rdf:rest Na6ba30b733d8483a90c26d825c1332a8
    79 N75a1b146110643b782b9b74e3a8e30c5 schema:issueNumber Suppl 1
    80 rdf:type schema:PublicationIssue
    81 N9e001a66ba0b4a849d3b6c1d852631ec schema:affiliation https://www.grid.ac/institutes/grid.424277.0
    82 schema:familyName Wieneke
    83 schema:givenName Ulrich
    84 rdf:type schema:Person
    85 Na1516ffa12304950aecf7a4aa5747a25 schema:name nlm_unique_id
    86 schema:value 101531992
    87 rdf:type schema:PropertyValue
    88 Na6ba30b733d8483a90c26d825c1332a8 rdf:first sg:person.0766734503.51
    89 rdf:rest N542ef4eeba404b49bdc85b49aaf9cc86
    90 Nb214803478ab45caad6c5912f371692d schema:volumeNumber 4
    91 rdf:type schema:PublicationVolume
    92 Nde86785dabda42548c64c8d52fb46076 schema:name pubmed_id
    93 schema:value 23734562
    94 rdf:type schema:PropertyValue
    95 Ne80a9971120045d2af02ab6c63db8d91 rdf:first sg:person.015666015012.74
    96 rdf:rest N6265f2aad5984700aa9e31d8e7f0c294
    97 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    98 schema:name Information and Computing Sciences
    99 rdf:type schema:DefinedTerm
    100 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
    101 schema:name Information Systems
    102 rdf:type schema:DefinedTerm
    103 sg:journal.1043573 schema:issn 2041-1480
    104 schema:name Journal of Biomedical Semantics
    105 rdf:type schema:Periodical
    106 sg:person.01127320076.40 schema:affiliation https://www.grid.ac/institutes/grid.4488.0
    107 schema:familyName Schroeder
    108 schema:givenName Michael
    109 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01127320076.40
    110 rdf:type schema:Person
    111 sg:person.014720756671.61 schema:affiliation https://www.grid.ac/institutes/grid.4488.0
    112 schema:familyName Tsatsaronis
    113 schema:givenName George
    114 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014720756671.61
    115 rdf:type schema:Person
    116 sg:person.015666015012.74 schema:affiliation https://www.grid.ac/institutes/grid.424277.0
    117 schema:familyName Eisinger
    118 schema:givenName Daniel
    119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015666015012.74
    120 rdf:type schema:Person
    121 sg:person.0766734503.51 schema:affiliation https://www.grid.ac/institutes/grid.424277.0
    122 schema:familyName Bundschus
    123 schema:givenName Markus
    124 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0766734503.51
    125 rdf:type schema:Person
    126 sg:pub.10.1007/978-3-642-15754-7_54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027780665
    127 https://doi.org/10.1007/978-3-642-15754-7_54
    128 rdf:type schema:CreativeWork
    129 sg:pub.10.1007/978-3-642-15754-7_59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022361915
    130 https://doi.org/10.1007/978-3-642-15754-7_59
    131 rdf:type schema:CreativeWork
    132 sg:pub.10.1007/978-3-642-19231-9_1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039616907
    133 https://doi.org/10.1007/978-3-642-19231-9_1
    134 rdf:type schema:CreativeWork
    135 sg:pub.10.1007/s10791-008-9074-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007640210
    136 https://doi.org/10.1007/s10791-008-9074-8
    137 rdf:type schema:CreativeWork
    138 sg:pub.10.1007/s11248-012-9641-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1021549882
    139 https://doi.org/10.1007/s11248-012-9641-z
    140 rdf:type schema:CreativeWork
    141 sg:pub.10.1186/1471-2105-4-20 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033906699
    142 https://doi.org/10.1186/1471-2105-4-20
    143 rdf:type schema:CreativeWork
    144 sg:pub.10.1186/2041-1480-3-s1-s2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012075462
    145 https://doi.org/10.1186/2041-1480-3-s1-s2
    146 rdf:type schema:CreativeWork
    147 https://doi.org/10.1002/hbm.22268 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001637414
    148 rdf:type schema:CreativeWork
    149 https://doi.org/10.1006/csla.1996.0011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029750983
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1016/0172-2190(90)90285-s schema:sameAs https://app.dimensions.ai/details/publication/pub.1009344425
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1016/j.eswa.2006.01.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023011065
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1016/j.ipm.2011.11.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052831817
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1016/j.wpi.2004.01.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002623207
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1016/j.wpi.2011.09.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012640331
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1016/j.wpi.2012.01.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026461049
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1016/j.wpi.2012.03.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014712620
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1016/s0172-2190(00)00073-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048824208
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1016/s0172-2190(00)00110-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043026371
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1016/s0172-2190(02)00026-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022771847
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1093/bioinformatics/bth291 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041160894
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1093/bioinformatics/btl302 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029305588
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1093/bioinformatics/btm557 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043760998
    176 rdf:type schema:CreativeWork
    177 https://doi.org/10.1093/bioinformatics/btp249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009025850
    178 rdf:type schema:CreativeWork
    179 https://doi.org/10.1093/nar/gki470 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051996212
    180 rdf:type schema:CreativeWork
    181 https://doi.org/10.1136/jamia.2001.0080317 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013384230
    182 rdf:type schema:CreativeWork
    183 https://doi.org/10.1145/1871888.1871894 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020330246
    184 rdf:type schema:CreativeWork
    185 https://doi.org/10.1145/945546.945547 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022313315
    186 rdf:type schema:CreativeWork
    187 https://doi.org/10.12927/cjnl.2012.22807 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064751877
    188 rdf:type schema:CreativeWork
    189 https://doi.org/10.2147/ott.s43122 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002094397
    190 rdf:type schema:CreativeWork
    191 https://doi.org/10.3163/1536-5050.100.3.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071062791
    192 rdf:type schema:CreativeWork
    193 https://doi.org/10.3169/itej1978.34.58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038443433
    194 rdf:type schema:CreativeWork
    195 https://doi.org/10.4018/978-1-59904-373-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1096031746
    196 rdf:type schema:CreativeWork
    197 https://doi.org/10.5260/chara.13.1.32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051272970
    198 rdf:type schema:CreativeWork
    199 https://www.grid.ac/institutes/grid.424277.0 schema:alternateName Roche (Germany)
    200 schema:name Roche Diagnostics GmbH, Nonnenwald 2, 82377, Penzberg, Germany
    201 TU Dresden, BIOTEC, Tatzberg 47/49, 01307, Dresden, Germany
    202 rdf:type schema:Organization
    203 https://www.grid.ac/institutes/grid.4488.0 schema:alternateName TU Dresden
    204 schema:name TU Dresden, BIOTEC, Tatzberg 47/49, 01307, Dresden, Germany
    205 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...