Impact of Polymerase Fidelity on Background Error Rates in Next-Generation Sequencing with Unique Molecular Identifiers/Barcodes View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Stefan Filges, Emiko Yamada, Anders Ståhlberg, Tony E. Godfrey

ABSTRACT

Liquid biopsy and detection of tumor-associated mutations in cell-free circulating DNA often requires the ability to identify single nucleotide variants at allele frequencies below 0.1%. Standard sequencing protocols cannot achieve this level of sensitivity due to background noise from DNA damage and polymerase induced errors. Addition of unique molecular identifiers allows identification and removal of errors responsible for this background noise. Theoretically, high fidelity enzymes will also reduce error rates in barcoded NGS but this has not been thoroughly explored. We evaluated the impact of polymerase fidelity on the magnitude of error reduction at different steps of barcoded NGS library construction. We find that barcoding itself displays largest impact on error reduction, even with low fidelity polymerases. Use of high fidelity polymerases in the barcoding step of library construction further suppresses error in barcoded NGS, and allows detection of variant alleles below 0.1% allele frequency. However, the improvement in error correction is modest and is not directly proportional to polymerase fidelity. Depending on the specific application, other polymerase characteristics such as multiplexing capacity, PCR efficiency, buffer requirements and ability to amplify targets with high GC content may outweigh the relatively small additional decrease in error afforded by ultra-high fidelity polymerases. More... »

PAGES

3503

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-39762-6

DOI

http://dx.doi.org/10.1038/s41598-019-39762-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112543997

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30837525


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/2008/1005", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Communications Technologies", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/10", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Technology", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Gothenburg", 
          "id": "https://www.grid.ac/institutes/grid.8761.8", 
          "name": [
            "Department of Pathology and Genetics, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Medicinaregatan 1F, 405 30, Gothenberg, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Filges", 
        "givenName": "Stefan", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Boston University School of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.475010.7", 
          "name": [
            "Department of Surgery, Boston University School of Medicine, 700 Albany Street, 02118, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yamada", 
        "givenName": "Emiko", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Sahlgrenska University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.1649.a", 
          "name": [
            "Department of Pathology and Genetics, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Medicinaregatan 1F, 405 30, Gothenberg, Sweden", 
            "Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden", 
            "Department of Clinical Pathology and Genetics, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "St\u00e5hlberg", 
        "givenName": "Anders", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Boston University School of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.475010.7", 
          "name": [
            "Department of Surgery, Boston University School of Medicine, 700 Albany Street, 02118, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Godfrey", 
        "givenName": "Tony E.", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1101/sqb.2009.74.027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001625713"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.biochem.69.1.497", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003361647"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.yexcr.2014.01.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011786034"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2014.170", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012801607", 
          "https://doi.org/10.1038/nprot.2014.170"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2353/jmoldx.2008.080027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018150853"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1105422108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025253093"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep08056", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025800612", 
          "https://doi.org/10.1038/srep08056"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-1119(91)90480-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025853437"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-1119(91)90480-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025853437"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1208715109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027689259"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt0594-506", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029775408", 
          "https://doi.org/10.1038/nbt0594-506"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkr861", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030946097"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkw224", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032762438"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4172/2469-9853.1000106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033784982"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg3655", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034338542", 
          "https://doi.org/10.1038/nrg3655"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkh271", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042220997"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1586/14737159.2015.1057124", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051271290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mrfmmm.2016.01.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051597597"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nm.3519", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051843226", 
          "https://doi.org/10.1038/nm.3519"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nm.3519", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051843226", 
          "https://doi.org/10.1038/nm.3519"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2017.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084129545", 
          "https://doi.org/10.1038/nprot.2017.006"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tibtech.2018.02.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101525535"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "Liquid biopsy and detection of tumor-associated mutations in cell-free circulating DNA often requires the ability to identify single nucleotide variants at allele frequencies below 0.1%. Standard sequencing protocols cannot achieve this level of sensitivity due to background noise from DNA damage and polymerase induced errors. Addition of unique molecular identifiers allows identification and removal of errors responsible for this background noise. Theoretically, high fidelity enzymes will also reduce error rates in barcoded NGS but this has not been thoroughly explored. We evaluated the impact of polymerase fidelity on the magnitude of error reduction at different steps of barcoded NGS library construction. We find that barcoding itself displays largest impact on error reduction, even with low fidelity polymerases. Use of high fidelity polymerases in the barcoding step of library construction further suppresses error in barcoded NGS, and allows detection of variant alleles below 0.1% allele frequency. However, the improvement in error correction is modest and is not directly proportional to polymerase fidelity. Depending on the specific application, other polymerase characteristics such as multiplexing capacity, PCR efficiency, buffer requirements and ability to amplify targets with high GC content may outweigh the relatively small additional decrease in error afforded by ultra-high fidelity polymerases.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/s41598-019-39762-6", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7762483", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.6499527", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "9"
      }
    ], 
    "name": "Impact of Polymerase Fidelity on Background Error Rates in Next-Generation Sequencing with Unique Molecular Identifiers/Barcodes", 
    "pagination": "3503", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "c875de986cb147ef2d9b4eb5544ece4daf3df85adb94d5f26abd1e96f25f05dd"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30837525"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41598-019-39762-6"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112543997"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41598-019-39762-6", 
      "https://app.dimensions.ai/details/publication/pub.1112543997"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T11:17", 
    "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/v90/0000000354_0000000354/records_11698_00000002.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/s41598-019-39762-6"
  }
]
 

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.10.1038/s41598-019-39762-6'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39762-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39762-6'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39762-6'


 

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

163 TRIPLES      21 PREDICATES      49 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41598-019-39762-6 schema:about anzsrc-for:10
2 anzsrc-for:1005
3 schema:author Ne3be0a4f11134aad80f2ba0a868396cf
4 schema:citation sg:pub.10.1038/nbt0594-506
5 sg:pub.10.1038/nm.3519
6 sg:pub.10.1038/nprot.2014.170
7 sg:pub.10.1038/nprot.2017.006
8 sg:pub.10.1038/nrg3655
9 sg:pub.10.1038/srep08056
10 https://doi.org/10.1016/0378-1119(91)90480-y
11 https://doi.org/10.1016/j.mrfmmm.2016.01.003
12 https://doi.org/10.1016/j.tibtech.2018.02.009
13 https://doi.org/10.1016/j.yexcr.2014.01.008
14 https://doi.org/10.1073/pnas.1105422108
15 https://doi.org/10.1073/pnas.1208715109
16 https://doi.org/10.1093/nar/gkh271
17 https://doi.org/10.1093/nar/gkr861
18 https://doi.org/10.1093/nar/gkw224
19 https://doi.org/10.1101/sqb.2009.74.027
20 https://doi.org/10.1146/annurev.biochem.69.1.497
21 https://doi.org/10.1586/14737159.2015.1057124
22 https://doi.org/10.2353/jmoldx.2008.080027
23 https://doi.org/10.4172/2469-9853.1000106
24 schema:datePublished 2019-12
25 schema:datePublishedReg 2019-12-01
26 schema:description Liquid biopsy and detection of tumor-associated mutations in cell-free circulating DNA often requires the ability to identify single nucleotide variants at allele frequencies below 0.1%. Standard sequencing protocols cannot achieve this level of sensitivity due to background noise from DNA damage and polymerase induced errors. Addition of unique molecular identifiers allows identification and removal of errors responsible for this background noise. Theoretically, high fidelity enzymes will also reduce error rates in barcoded NGS but this has not been thoroughly explored. We evaluated the impact of polymerase fidelity on the magnitude of error reduction at different steps of barcoded NGS library construction. We find that barcoding itself displays largest impact on error reduction, even with low fidelity polymerases. Use of high fidelity polymerases in the barcoding step of library construction further suppresses error in barcoded NGS, and allows detection of variant alleles below 0.1% allele frequency. However, the improvement in error correction is modest and is not directly proportional to polymerase fidelity. Depending on the specific application, other polymerase characteristics such as multiplexing capacity, PCR efficiency, buffer requirements and ability to amplify targets with high GC content may outweigh the relatively small additional decrease in error afforded by ultra-high fidelity polymerases.
27 schema:genre research_article
28 schema:inLanguage en
29 schema:isAccessibleForFree true
30 schema:isPartOf Nc3c5321fafb4408b85a12d94287f0f05
31 Nf186cff592d8431abc21bf62108cd669
32 sg:journal.1045337
33 schema:name Impact of Polymerase Fidelity on Background Error Rates in Next-Generation Sequencing with Unique Molecular Identifiers/Barcodes
34 schema:pagination 3503
35 schema:productId N16053e2673484206b16761ef20e0bdff
36 N80f77eddf2a0449a874e134bb05cfccf
37 Nc6a10e05f0d847f38cd76967c76855f3
38 Nc98dee37662444b6aab902e738789048
39 Nf25e6f8df28e4ea1b2a366005d431c18
40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112543997
41 https://doi.org/10.1038/s41598-019-39762-6
42 schema:sdDatePublished 2019-04-11T11:17
43 schema:sdLicense https://scigraph.springernature.com/explorer/license/
44 schema:sdPublisher N04d27bd3a1d74a6080d601754baaf769
45 schema:url https://www.nature.com/articles/s41598-019-39762-6
46 sgo:license sg:explorer/license/
47 sgo:sdDataset articles
48 rdf:type schema:ScholarlyArticle
49 N04d27bd3a1d74a6080d601754baaf769 schema:name Springer Nature - SN SciGraph project
50 rdf:type schema:Organization
51 N0d672886fefb4ddbb3a15d082e885195 rdf:first N5915a8ba9a1c45e1a252c7fae3ed681c
52 rdf:rest Nb72470f5e1e74c4092f11f7f4a54167b
53 N16053e2673484206b16761ef20e0bdff schema:name doi
54 schema:value 10.1038/s41598-019-39762-6
55 rdf:type schema:PropertyValue
56 N1dd6be643a8f49c784bb07ecf16fbafe schema:affiliation https://www.grid.ac/institutes/grid.8761.8
57 schema:familyName Filges
58 schema:givenName Stefan
59 rdf:type schema:Person
60 N4d3983c2e62747ac9b8f2f440ba1e5cb rdf:first N5532f6bd0d0f4df3b71b5b70479cc9db
61 rdf:rest N0d672886fefb4ddbb3a15d082e885195
62 N5532f6bd0d0f4df3b71b5b70479cc9db schema:affiliation https://www.grid.ac/institutes/grid.475010.7
63 schema:familyName Yamada
64 schema:givenName Emiko
65 rdf:type schema:Person
66 N5915a8ba9a1c45e1a252c7fae3ed681c schema:affiliation https://www.grid.ac/institutes/grid.1649.a
67 schema:familyName Ståhlberg
68 schema:givenName Anders
69 rdf:type schema:Person
70 N80f77eddf2a0449a874e134bb05cfccf schema:name pubmed_id
71 schema:value 30837525
72 rdf:type schema:PropertyValue
73 Nb72470f5e1e74c4092f11f7f4a54167b rdf:first Nc60727c61f044d719700589417e93f4f
74 rdf:rest rdf:nil
75 Nc3c5321fafb4408b85a12d94287f0f05 schema:volumeNumber 9
76 rdf:type schema:PublicationVolume
77 Nc60727c61f044d719700589417e93f4f schema:affiliation https://www.grid.ac/institutes/grid.475010.7
78 schema:familyName Godfrey
79 schema:givenName Tony E.
80 rdf:type schema:Person
81 Nc6a10e05f0d847f38cd76967c76855f3 schema:name readcube_id
82 schema:value c875de986cb147ef2d9b4eb5544ece4daf3df85adb94d5f26abd1e96f25f05dd
83 rdf:type schema:PropertyValue
84 Nc98dee37662444b6aab902e738789048 schema:name dimensions_id
85 schema:value pub.1112543997
86 rdf:type schema:PropertyValue
87 Ne3be0a4f11134aad80f2ba0a868396cf rdf:first N1dd6be643a8f49c784bb07ecf16fbafe
88 rdf:rest N4d3983c2e62747ac9b8f2f440ba1e5cb
89 Nf186cff592d8431abc21bf62108cd669 schema:issueNumber 1
90 rdf:type schema:PublicationIssue
91 Nf25e6f8df28e4ea1b2a366005d431c18 schema:name nlm_unique_id
92 schema:value 101563288
93 rdf:type schema:PropertyValue
94 anzsrc-for:10 schema:inDefinedTermSet anzsrc-for:
95 schema:name Technology
96 rdf:type schema:DefinedTerm
97 anzsrc-for:1005 schema:inDefinedTermSet anzsrc-for:
98 schema:name Communications Technologies
99 rdf:type schema:DefinedTerm
100 sg:grant.6499527 http://pending.schema.org/fundedItem sg:pub.10.1038/s41598-019-39762-6
101 rdf:type schema:MonetaryGrant
102 sg:grant.7762483 http://pending.schema.org/fundedItem sg:pub.10.1038/s41598-019-39762-6
103 rdf:type schema:MonetaryGrant
104 sg:journal.1045337 schema:issn 2045-2322
105 schema:name Scientific Reports
106 rdf:type schema:Periodical
107 sg:pub.10.1038/nbt0594-506 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029775408
108 https://doi.org/10.1038/nbt0594-506
109 rdf:type schema:CreativeWork
110 sg:pub.10.1038/nm.3519 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051843226
111 https://doi.org/10.1038/nm.3519
112 rdf:type schema:CreativeWork
113 sg:pub.10.1038/nprot.2014.170 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012801607
114 https://doi.org/10.1038/nprot.2014.170
115 rdf:type schema:CreativeWork
116 sg:pub.10.1038/nprot.2017.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084129545
117 https://doi.org/10.1038/nprot.2017.006
118 rdf:type schema:CreativeWork
119 sg:pub.10.1038/nrg3655 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034338542
120 https://doi.org/10.1038/nrg3655
121 rdf:type schema:CreativeWork
122 sg:pub.10.1038/srep08056 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025800612
123 https://doi.org/10.1038/srep08056
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/0378-1119(91)90480-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1025853437
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.mrfmmm.2016.01.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051597597
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.tibtech.2018.02.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101525535
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.yexcr.2014.01.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011786034
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1073/pnas.1105422108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025253093
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1073/pnas.1208715109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027689259
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1093/nar/gkh271 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042220997
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1093/nar/gkr861 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030946097
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1093/nar/gkw224 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032762438
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1101/sqb.2009.74.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001625713
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1146/annurev.biochem.69.1.497 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003361647
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1586/14737159.2015.1057124 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051271290
148 rdf:type schema:CreativeWork
149 https://doi.org/10.2353/jmoldx.2008.080027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018150853
150 rdf:type schema:CreativeWork
151 https://doi.org/10.4172/2469-9853.1000106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033784982
152 rdf:type schema:CreativeWork
153 https://www.grid.ac/institutes/grid.1649.a schema:alternateName Sahlgrenska University Hospital
154 schema:name Department of Clinical Pathology and Genetics, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden
155 Department of Pathology and Genetics, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Medicinaregatan 1F, 405 30, Gothenberg, Sweden
156 Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
157 rdf:type schema:Organization
158 https://www.grid.ac/institutes/grid.475010.7 schema:alternateName Boston University School of Medicine
159 schema:name Department of Surgery, Boston University School of Medicine, 700 Albany Street, 02118, Boston, MA, USA
160 rdf:type schema:Organization
161 https://www.grid.ac/institutes/grid.8761.8 schema:alternateName University of Gothenburg
162 schema:name Department of Pathology and Genetics, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Medicinaregatan 1F, 405 30, Gothenberg, Sweden
163 rdf:type schema:Organization
 




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


...