Molecular Classifications View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2007

AUTHORS

Gregory N. Fuller

ABSTRACT

The field of glioma classification is currently entering a new era with the introduction of paradigms based on molecular information. Rather than supplanting traditional morphology-based classification schemes, it is anticipated that emerging molecular biologic, genomic, transcriptomic, and proteomic data will complement and augment existing morphologic and immunophenotypic data, providing for a more accurate and refined stratification of glioma patients for directed therapies and for the resolution of several problematic issues inherent in histological classifications. Two different approaches are contributing to the improvement of glioma stratification. The first is the analysis of alterations of a limited number of genes or gene products of recently demonstrated impact on patient survival and response to therapy, such as deletion status of chromosomes 1p and 19q in oligodendroglial tumors, and O(6)-methylguanine-DNA methyltransferase (MGMT) promoter methylation in glioblastoma. The second is a more comprehensive analysis of the tumor genome, transcriptome, or proteome, which may in itself provide refined subclassification, or may identify specific relevant biomolecules for use in the single gene analysis approach. Both paradigms have already exerted a tangible and growing impact on glioma classification, yet it is highly likely that we have only just begun to exploit their potential contributions. More... »

PAGES

37-42

Book

TITLE

High-Grade Gliomas

ISBN

978-1-58829-511-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-59745-185-7_2

DOI

http://dx.doi.org/10.1007/978-1-59745-185-7_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015248565


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/2008/0604", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Genetics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "The University of Texas MD Anderson Cancer Center", 
          "id": "https://www.grid.ac/institutes/grid.240145.6", 
          "name": [
            "Department of Pathology, MD Anderson Cancer Center, Houston, TX"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fuller", 
        "givenName": "Gregory N.", 
        "id": "sg:person.013732343337.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013732343337.08"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/1097-0142(19881115)62:10<2152::aid-cncr2820621015>3.0.co;2-t", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002422298"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jnen/64.1.10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002619839"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jnen/62.2.111", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003403745"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrn1518", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006061461", 
          "https://doi.org/10.1038/nrn1518"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrn1518", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006061461", 
          "https://doi.org/10.1038/nrn1518"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/0008-5472.can-04-0452", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007295205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/1097-0142(19850901)56:5<1106::aid-cncr2820560525>3.0.co;2-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007980454"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/gcc.20108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008069936"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-03-0384", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011849209"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cncr.20828", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012509185"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jnci/90.19.1473", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020269354"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cncr.21338", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027141107"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cncr.21338", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027141107"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/0008-5472.can-04-2921", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027812355"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/ijc.21121", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027907249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/ijc.21121", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027907249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa043331", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029207836"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11060-004-2748-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029929197", 
          "https://doi.org/10.1007/s11060-004-2748-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.onc.1206753", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030479340", 
          "https://doi.org/10.1038/sj.onc.1206753"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.onc.1206753", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030479340", 
          "https://doi.org/10.1038/sj.onc.1206753"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1750-3639.2002.tb00427.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037188811"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00019052-200412000-00006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039445652"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00019052-200412000-00006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039445652"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/0008-5472.can-03-1254", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043375091"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/0008-5472.can-03-1254", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043375091"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/path.837", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044689180"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.onc.1206344", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045257811", 
          "https://doi.org/10.1038/sj.onc.1206344"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.onc.1206344", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045257811", 
          "https://doi.org/10.1038/sj.onc.1206344"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/1097-0142(19830801)52:3<550::aid-cncr2820520327>3.0.co;2-c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046864391"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa043330", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052112015"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.14670/hh-15.971", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074691415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1074896187", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1075203361", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1075262336", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1076588037", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2007", 
    "datePublishedReg": "2007-01-01", 
    "description": "The field of glioma classification is currently entering a new era with the introduction of paradigms based on molecular information. Rather than supplanting traditional morphology-based classification schemes, it is anticipated that emerging molecular biologic, genomic, transcriptomic, and proteomic data will complement and augment existing morphologic and immunophenotypic data, providing for a more accurate and refined stratification of glioma patients for directed therapies and for the resolution of several problematic issues inherent in histological classifications. Two different approaches are contributing to the improvement of glioma stratification. The first is the analysis of alterations of a limited number of genes or gene products of recently demonstrated impact on patient survival and response to therapy, such as deletion status of chromosomes 1p and 19q in oligodendroglial tumors, and O(6)-methylguanine-DNA methyltransferase (MGMT) promoter methylation in glioblastoma. The second is a more comprehensive analysis of the tumor genome, transcriptome, or proteome, which may in itself provide refined subclassification, or may identify specific relevant biomolecules for use in the single gene analysis approach. Both paradigms have already exerted a tangible and growing impact on glioma classification, yet it is highly likely that we have only just begun to exploit their potential contributions.", 
    "editor": [
      {
        "familyName": "Barnett", 
        "givenName": "Gene H.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-59745-185-7_2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-1-58829-511-8"
      ], 
      "name": "High-Grade Gliomas", 
      "type": "Book"
    }, 
    "name": "Molecular Classifications", 
    "pagination": "37-42", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-59745-185-7_2"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "48a69d7c3875eb33ab4a95368e8d85516822803c0d6ecd1d4fc688f2c726bcdc"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1015248565"
        ]
      }
    ], 
    "publisher": {
      "location": "Totowa, NJ", 
      "name": "Humana Press", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-59745-185-7_2", 
      "https://app.dimensions.ai/details/publication/pub.1015248565"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T05:49", 
    "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/v90/0000000347_0000000347/records_89824_00000000.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-1-59745-185-7_2"
  }
]
 

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.10.1007/978-1-59745-185-7_2'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-59745-185-7_2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-59745-185-7_2'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-59745-185-7_2'


 

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

148 TRIPLES      23 PREDICATES      55 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-59745-185-7_2 schema:about anzsrc-for:06
2 anzsrc-for:0604
3 schema:author N5a76348e7b3b480fb8dc942002047421
4 schema:citation sg:pub.10.1007/s11060-004-2748-1
5 sg:pub.10.1038/nrn1518
6 sg:pub.10.1038/sj.onc.1206344
7 sg:pub.10.1038/sj.onc.1206753
8 https://app.dimensions.ai/details/publication/pub.1074896187
9 https://app.dimensions.ai/details/publication/pub.1075203361
10 https://app.dimensions.ai/details/publication/pub.1075262336
11 https://app.dimensions.ai/details/publication/pub.1076588037
12 https://doi.org/10.1002/1097-0142(19830801)52:3<550::aid-cncr2820520327>3.0.co;2-c
13 https://doi.org/10.1002/1097-0142(19850901)56:5<1106::aid-cncr2820560525>3.0.co;2-2
14 https://doi.org/10.1002/1097-0142(19881115)62:10<2152::aid-cncr2820621015>3.0.co;2-t
15 https://doi.org/10.1002/cncr.20828
16 https://doi.org/10.1002/cncr.21338
17 https://doi.org/10.1002/gcc.20108
18 https://doi.org/10.1002/ijc.21121
19 https://doi.org/10.1002/path.837
20 https://doi.org/10.1056/nejmoa043330
21 https://doi.org/10.1056/nejmoa043331
22 https://doi.org/10.1093/jnci/90.19.1473
23 https://doi.org/10.1093/jnen/62.2.111
24 https://doi.org/10.1093/jnen/64.1.10
25 https://doi.org/10.1097/00019052-200412000-00006
26 https://doi.org/10.1111/j.1750-3639.2002.tb00427.x
27 https://doi.org/10.1158/0008-5472.can-03-1254
28 https://doi.org/10.1158/0008-5472.can-04-0452
29 https://doi.org/10.1158/0008-5472.can-04-2921
30 https://doi.org/10.1158/1078-0432.ccr-03-0384
31 https://doi.org/10.14670/hh-15.971
32 schema:datePublished 2007
33 schema:datePublishedReg 2007-01-01
34 schema:description The field of glioma classification is currently entering a new era with the introduction of paradigms based on molecular information. Rather than supplanting traditional morphology-based classification schemes, it is anticipated that emerging molecular biologic, genomic, transcriptomic, and proteomic data will complement and augment existing morphologic and immunophenotypic data, providing for a more accurate and refined stratification of glioma patients for directed therapies and for the resolution of several problematic issues inherent in histological classifications. Two different approaches are contributing to the improvement of glioma stratification. The first is the analysis of alterations of a limited number of genes or gene products of recently demonstrated impact on patient survival and response to therapy, such as deletion status of chromosomes 1p and 19q in oligodendroglial tumors, and O(6)-methylguanine-DNA methyltransferase (MGMT) promoter methylation in glioblastoma. The second is a more comprehensive analysis of the tumor genome, transcriptome, or proteome, which may in itself provide refined subclassification, or may identify specific relevant biomolecules for use in the single gene analysis approach. Both paradigms have already exerted a tangible and growing impact on glioma classification, yet it is highly likely that we have only just begun to exploit their potential contributions.
35 schema:editor N70a4f8d67fb44aabb209744be9f35bc2
36 schema:genre chapter
37 schema:inLanguage en
38 schema:isAccessibleForFree false
39 schema:isPartOf N7ff57b826850404abe51032f70898146
40 schema:name Molecular Classifications
41 schema:pagination 37-42
42 schema:productId N380492d378f943bb87cec4924222caad
43 N5474e23574f549dab69ab8c42026cf8d
44 N76b34d9e1d1147f48cdcd0ea75260cdb
45 schema:publisher N2afbce8e866d4a7a8518cbac2c2cf38b
46 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015248565
47 https://doi.org/10.1007/978-1-59745-185-7_2
48 schema:sdDatePublished 2019-04-16T05:49
49 schema:sdLicense https://scigraph.springernature.com/explorer/license/
50 schema:sdPublisher Nf7d46269472f42c999b34095915c6355
51 schema:url https://link.springer.com/10.1007%2F978-1-59745-185-7_2
52 sgo:license sg:explorer/license/
53 sgo:sdDataset chapters
54 rdf:type schema:Chapter
55 N2afbce8e866d4a7a8518cbac2c2cf38b schema:location Totowa, NJ
56 schema:name Humana Press
57 rdf:type schema:Organisation
58 N380492d378f943bb87cec4924222caad schema:name doi
59 schema:value 10.1007/978-1-59745-185-7_2
60 rdf:type schema:PropertyValue
61 N46ff459414a745aa80021aa1181e1467 schema:familyName Barnett
62 schema:givenName Gene H.
63 rdf:type schema:Person
64 N5474e23574f549dab69ab8c42026cf8d schema:name readcube_id
65 schema:value 48a69d7c3875eb33ab4a95368e8d85516822803c0d6ecd1d4fc688f2c726bcdc
66 rdf:type schema:PropertyValue
67 N5a76348e7b3b480fb8dc942002047421 rdf:first sg:person.013732343337.08
68 rdf:rest rdf:nil
69 N70a4f8d67fb44aabb209744be9f35bc2 rdf:first N46ff459414a745aa80021aa1181e1467
70 rdf:rest rdf:nil
71 N76b34d9e1d1147f48cdcd0ea75260cdb schema:name dimensions_id
72 schema:value pub.1015248565
73 rdf:type schema:PropertyValue
74 N7ff57b826850404abe51032f70898146 schema:isbn 978-1-58829-511-8
75 schema:name High-Grade Gliomas
76 rdf:type schema:Book
77 Nf7d46269472f42c999b34095915c6355 schema:name Springer Nature - SN SciGraph project
78 rdf:type schema:Organization
79 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
80 schema:name Biological Sciences
81 rdf:type schema:DefinedTerm
82 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
83 schema:name Genetics
84 rdf:type schema:DefinedTerm
85 sg:person.013732343337.08 schema:affiliation https://www.grid.ac/institutes/grid.240145.6
86 schema:familyName Fuller
87 schema:givenName Gregory N.
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013732343337.08
89 rdf:type schema:Person
90 sg:pub.10.1007/s11060-004-2748-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029929197
91 https://doi.org/10.1007/s11060-004-2748-1
92 rdf:type schema:CreativeWork
93 sg:pub.10.1038/nrn1518 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006061461
94 https://doi.org/10.1038/nrn1518
95 rdf:type schema:CreativeWork
96 sg:pub.10.1038/sj.onc.1206344 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045257811
97 https://doi.org/10.1038/sj.onc.1206344
98 rdf:type schema:CreativeWork
99 sg:pub.10.1038/sj.onc.1206753 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030479340
100 https://doi.org/10.1038/sj.onc.1206753
101 rdf:type schema:CreativeWork
102 https://app.dimensions.ai/details/publication/pub.1074896187 schema:CreativeWork
103 https://app.dimensions.ai/details/publication/pub.1075203361 schema:CreativeWork
104 https://app.dimensions.ai/details/publication/pub.1075262336 schema:CreativeWork
105 https://app.dimensions.ai/details/publication/pub.1076588037 schema:CreativeWork
106 https://doi.org/10.1002/1097-0142(19830801)52:3<550::aid-cncr2820520327>3.0.co;2-c schema:sameAs https://app.dimensions.ai/details/publication/pub.1046864391
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1002/1097-0142(19850901)56:5<1106::aid-cncr2820560525>3.0.co;2-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007980454
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1002/1097-0142(19881115)62:10<2152::aid-cncr2820621015>3.0.co;2-t schema:sameAs https://app.dimensions.ai/details/publication/pub.1002422298
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1002/cncr.20828 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012509185
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1002/cncr.21338 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027141107
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1002/gcc.20108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008069936
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1002/ijc.21121 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027907249
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1002/path.837 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044689180
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1056/nejmoa043330 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052112015
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1056/nejmoa043331 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029207836
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1093/jnci/90.19.1473 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020269354
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1093/jnen/62.2.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003403745
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1093/jnen/64.1.10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002619839
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1097/00019052-200412000-00006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039445652
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1111/j.1750-3639.2002.tb00427.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1037188811
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1158/0008-5472.can-03-1254 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043375091
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1158/0008-5472.can-04-0452 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007295205
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1158/0008-5472.can-04-2921 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027812355
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1158/1078-0432.ccr-03-0384 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011849209
143 rdf:type schema:CreativeWork
144 https://doi.org/10.14670/hh-15.971 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074691415
145 rdf:type schema:CreativeWork
146 https://www.grid.ac/institutes/grid.240145.6 schema:alternateName The University of Texas MD Anderson Cancer Center
147 schema:name Department of Pathology, MD Anderson Cancer Center, Houston, TX
148 rdf:type schema:Organization
 




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


...