AceView: a comprehensive cDNA-supported gene and transcripts annotation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2006-08

AUTHORS

Danielle Thierry-Mieg, Jean Thierry-Mieg

ABSTRACT

BACKGROUND: Regions covering one percent of the genome, selected by ENCODE for extensive analysis, were annotated by the HAVANA/Gencode group with high quality transcripts, thus defining a benchmark. The ENCODE Genome Annotation Assessment Project (EGASP) competition aimed at reproducing Gencode and finding new genes. The organizers evaluated the protein predictions in depth. We present a complementary analysis of the mRNAs, including alternative transcript variants. RESULTS: We evaluate 25 gene tracks from the University of California Santa Cruz (UCSC) genome browser. We either distinguish or collapse the alternative splice variants, and compare the genomic coordinates of exons, introns and nucleotides. Whole mRNA models, seen as chains of introns, are sorted to find the best matching pairs, and compared so that each mRNA is used only once. At the mRNA level, AceView is by far the closest to Gencode: the vast majority of transcripts of the two methods, including alternative variants, are identical. At the protein level, however, due to a lack of experimental data, our predictions differ: Gencode annotates proteins in only 41% of the mRNAs whereas AceView does so in virtually all. We describe the driving principles of AceView, and how, by performing hand-supervised automatic annotation, we solve the combinatorial splicing problem and summarize all of GenBank, dbEST and RefSeq into a genome-wide non-redundant but comprehensive cDNA-supported transcriptome. AceView accuracy is now validated by Gencode. CONCLUSION: Relative to a consensus mRNA catalog constructed from all evidence-based annotations, Gencode and AceView have 81% and 84% sensitivity, and 74% and 73% specificity, respectively. This close agreement validates a richer view of the human transcriptome, with three to five times more transcripts than in UCSC Known Genes (sensitivity 28%), RefSeq (sensitivity 21%) or Ensembl (sensitivity 19%). More... »

PAGES

s12

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/gb-2006-7-s1-s12

DOI

http://dx.doi.org/10.1186/gb-2006-7-s1-s12

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1050280568

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16925834


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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computational Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "DNA, Complementary", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Exons", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genes", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genomics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Introns", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Nucleotides", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "RNA, Messenger", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sequence Analysis, DNA", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sequence Analysis, Protein", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sequence Analysis, RNA", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Software", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National Institute of Arthritis and Musculoskeletal and Skin Diseases", 
          "id": "https://www.grid.ac/institutes/grid.420086.8", 
          "name": [
            "National Center for Biotechnology Information, National Library of Medicine, NIH, 20894, Bethesda, MD, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Thierry-Mieg", 
        "givenName": "Danielle", 
        "id": "sg:person.0666340601.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0666340601.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Institute of Arthritis and Musculoskeletal and Skin Diseases", 
          "id": "https://www.grid.ac/institutes/grid.420086.8", 
          "name": [
            "National Center for Biotechnology Information, National Library of Medicine, NIH, 20894, Bethesda, MD, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Thierry-Mieg", 
        "givenName": "Jean", 
        "id": "sg:person.01002567201.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01002567201.20"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1038/sj.emboj.7601023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001779862"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/sj.emboj.7601023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001779862"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/85913", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002028191", 
          "https://doi.org/10.1038/85913"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/85913", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002028191", 
          "https://doi.org/10.1038/85913"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/jcs.01701", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005027838"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkj144", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005091941"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/mcb.19.12.8505", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006841201"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.3729105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011381905"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature03001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013534924", 
          "https://doi.org/10.1038/nature03001"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature03001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013534924", 
          "https://doi.org/10.1038/nature03001"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1429", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015685857", 
          "https://doi.org/10.1038/ng1429"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1429", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015685857", 
          "https://doi.org/10.1038/ng1429"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1111443", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016370374"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018946050", 
          "https://doi.org/10.1038/ng1285"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018946050", 
          "https://doi.org/10.1038/ng1285"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth0805-575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020319965", 
          "https://doi.org/10.1038/nmeth0805-575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth0805-575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020319965", 
          "https://doi.org/10.1038/nmeth0805-575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth0805-575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020319965", 
          "https://doi.org/10.1038/nmeth0805-575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.2384604", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021287423"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tig.2005.01.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024789565"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/embo-reports/kve085", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026461752"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0378-1119(02)01056-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028350454"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0378-1119(02)01056-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028350454"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1105136", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031973383"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.4039406", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033353829"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1074/jbc.m511265200", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036174700"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/mcb.9.11.5073", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039128892"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0248-4900(03)00033-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047504577"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2006-7-s1-s2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048969371", 
          "https://doi.org/10.1186/gb-2006-7-s1-s2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2174/138920306776359795", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069179117"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1083300833", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2006-08", 
    "datePublishedReg": "2006-08-01", 
    "description": "BACKGROUND: Regions covering one percent of the genome, selected by ENCODE for extensive analysis, were annotated by the HAVANA/Gencode group with high quality transcripts, thus defining a benchmark. The ENCODE Genome Annotation Assessment Project (EGASP) competition aimed at reproducing Gencode and finding new genes. The organizers evaluated the protein predictions in depth. We present a complementary analysis of the mRNAs, including alternative transcript variants.\nRESULTS: We evaluate 25 gene tracks from the University of California Santa Cruz (UCSC) genome browser. We either distinguish or collapse the alternative splice variants, and compare the genomic coordinates of exons, introns and nucleotides. Whole mRNA models, seen as chains of introns, are sorted to find the best matching pairs, and compared so that each mRNA is used only once. At the mRNA level, AceView is by far the closest to Gencode: the vast majority of transcripts of the two methods, including alternative variants, are identical. At the protein level, however, due to a lack of experimental data, our predictions differ: Gencode annotates proteins in only 41% of the mRNAs whereas AceView does so in virtually all. We describe the driving principles of AceView, and how, by performing hand-supervised automatic annotation, we solve the combinatorial splicing problem and summarize all of GenBank, dbEST and RefSeq into a genome-wide non-redundant but comprehensive cDNA-supported transcriptome. AceView accuracy is now validated by Gencode.\nCONCLUSION: Relative to a consensus mRNA catalog constructed from all evidence-based annotations, Gencode and AceView have 81% and 84% sensitivity, and 74% and 73% specificity, respectively. This close agreement validates a richer view of the human transcriptome, with three to five times more transcripts than in UCSC Known Genes (sensitivity 28%), RefSeq (sensitivity 21%) or Ensembl (sensitivity 19%).", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/gb-2006-7-s1-s12", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1023439", 
        "issn": [
          "1474-760X", 
          "1465-6906"
        ], 
        "name": "Genome Biology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "Suppl 1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "7"
      }
    ], 
    "name": "AceView: a comprehensive cDNA-supported gene and transcripts annotation", 
    "pagination": "s12", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ef85b30e3fd958bdc092d6aa2e72800bb59cfcae9a253a066f00f5fcf249a981"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "16925834"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100960660"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/gb-2006-7-s1-s12"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1050280568"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/gb-2006-7-s1-s12", 
      "https://app.dimensions.ai/details/publication/pub.1050280568"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T00:17", 
    "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/v90/0000000001_0000000264/records_8695_00000516.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2Fgb-2006-7-s1-s12"
  }
]
 

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/gb-2006-7-s1-s12'

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/gb-2006-7-s1-s12'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/gb-2006-7-s1-s12'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/gb-2006-7-s1-s12'


 

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

206 TRIPLES      21 PREDICATES      66 URIs      35 LITERALS      23 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/gb-2006-7-s1-s12 schema:about N1edf93c44fad4fdcb823b0519f03f71c
2 N22ec5558e0e34e22a807169466f486c8
3 N28645624bc374c37a77b9995dd7b03fb
4 N5203671630d04404a3e191aacdfd6929
5 N73bb751c1d9344ec9ba368a283798196
6 N7c9f613f27674f2d92e1dc4a39d0af2d
7 N8aa7b66ecf6149d9801f1fcf7e915e24
8 N90013f5211554243b7306821dcd57426
9 N9c216a8577294a279da353ebef685b94
10 Nba7f1e715e5b4b55a8646c2332d55da5
11 Nbe751165bce94938a573a9448a185bc7
12 Ndf6eecb717c74d1e977a93d8057e20c4
13 Ne538f345de2f443f95e85478f880d27a
14 Nf5a520b206ef4c1e9b02f9ca7827873f
15 anzsrc-for:06
16 anzsrc-for:0604
17 schema:author Nfe3ad44ccbc44895a504b09145e3d4dc
18 schema:citation sg:pub.10.1038/85913
19 sg:pub.10.1038/nature03001
20 sg:pub.10.1038/ng1285
21 sg:pub.10.1038/ng1429
22 sg:pub.10.1038/nmeth0805-575
23 sg:pub.10.1186/gb-2006-7-s1-s2
24 https://app.dimensions.ai/details/publication/pub.1083300833
25 https://doi.org/10.1016/j.tig.2005.01.007
26 https://doi.org/10.1016/s0248-4900(03)00033-9
27 https://doi.org/10.1016/s0378-1119(02)01056-9
28 https://doi.org/10.1038/sj.emboj.7601023
29 https://doi.org/10.1074/jbc.m511265200
30 https://doi.org/10.1093/embo-reports/kve085
31 https://doi.org/10.1093/nar/gkj144
32 https://doi.org/10.1101/gr.2384604
33 https://doi.org/10.1101/gr.3729105
34 https://doi.org/10.1101/gr.4039406
35 https://doi.org/10.1126/science.1105136
36 https://doi.org/10.1126/science.1111443
37 https://doi.org/10.1128/mcb.19.12.8505
38 https://doi.org/10.1128/mcb.9.11.5073
39 https://doi.org/10.1242/jcs.01701
40 https://doi.org/10.2174/138920306776359795
41 schema:datePublished 2006-08
42 schema:datePublishedReg 2006-08-01
43 schema:description BACKGROUND: Regions covering one percent of the genome, selected by ENCODE for extensive analysis, were annotated by the HAVANA/Gencode group with high quality transcripts, thus defining a benchmark. The ENCODE Genome Annotation Assessment Project (EGASP) competition aimed at reproducing Gencode and finding new genes. The organizers evaluated the protein predictions in depth. We present a complementary analysis of the mRNAs, including alternative transcript variants. RESULTS: We evaluate 25 gene tracks from the University of California Santa Cruz (UCSC) genome browser. We either distinguish or collapse the alternative splice variants, and compare the genomic coordinates of exons, introns and nucleotides. Whole mRNA models, seen as chains of introns, are sorted to find the best matching pairs, and compared so that each mRNA is used only once. At the mRNA level, AceView is by far the closest to Gencode: the vast majority of transcripts of the two methods, including alternative variants, are identical. At the protein level, however, due to a lack of experimental data, our predictions differ: Gencode annotates proteins in only 41% of the mRNAs whereas AceView does so in virtually all. We describe the driving principles of AceView, and how, by performing hand-supervised automatic annotation, we solve the combinatorial splicing problem and summarize all of GenBank, dbEST and RefSeq into a genome-wide non-redundant but comprehensive cDNA-supported transcriptome. AceView accuracy is now validated by Gencode. CONCLUSION: Relative to a consensus mRNA catalog constructed from all evidence-based annotations, Gencode and AceView have 81% and 84% sensitivity, and 74% and 73% specificity, respectively. This close agreement validates a richer view of the human transcriptome, with three to five times more transcripts than in UCSC Known Genes (sensitivity 28%), RefSeq (sensitivity 21%) or Ensembl (sensitivity 19%).
44 schema:genre research_article
45 schema:inLanguage en
46 schema:isAccessibleForFree true
47 schema:isPartOf N9a16e6e0322d4a7e886e22e7ecce7fa1
48 Nafd126653cc94e7dab3773903ce43795
49 sg:journal.1023439
50 schema:name AceView: a comprehensive cDNA-supported gene and transcripts annotation
51 schema:pagination s12
52 schema:productId N2912d08563c44535b6ff66c3fb811833
53 N41cd1a21f74c4e33a609289f0ca10afc
54 N4c3e45c25fab45cb963c1c87e8c243c5
55 N5485349df3fd425d8d7dac4bf642ac53
56 Nff02b5c901c74fe6ab60def8958024a8
57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050280568
58 https://doi.org/10.1186/gb-2006-7-s1-s12
59 schema:sdDatePublished 2019-04-11T00:17
60 schema:sdLicense https://scigraph.springernature.com/explorer/license/
61 schema:sdPublisher N01726fcab917438892060f91c4b30122
62 schema:url http://link.springer.com/10.1186%2Fgb-2006-7-s1-s12
63 sgo:license sg:explorer/license/
64 sgo:sdDataset articles
65 rdf:type schema:ScholarlyArticle
66 N01726fcab917438892060f91c4b30122 schema:name Springer Nature - SN SciGraph project
67 rdf:type schema:Organization
68 N1edf93c44fad4fdcb823b0519f03f71c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
69 schema:name Models, Genetic
70 rdf:type schema:DefinedTerm
71 N22ec5558e0e34e22a807169466f486c8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
72 schema:name Sequence Analysis, Protein
73 rdf:type schema:DefinedTerm
74 N28645624bc374c37a77b9995dd7b03fb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
75 schema:name Sequence Analysis, DNA
76 rdf:type schema:DefinedTerm
77 N2912d08563c44535b6ff66c3fb811833 schema:name doi
78 schema:value 10.1186/gb-2006-7-s1-s12
79 rdf:type schema:PropertyValue
80 N41cd1a21f74c4e33a609289f0ca10afc schema:name dimensions_id
81 schema:value pub.1050280568
82 rdf:type schema:PropertyValue
83 N4c3e45c25fab45cb963c1c87e8c243c5 schema:name readcube_id
84 schema:value ef85b30e3fd958bdc092d6aa2e72800bb59cfcae9a253a066f00f5fcf249a981
85 rdf:type schema:PropertyValue
86 N5203671630d04404a3e191aacdfd6929 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
87 schema:name Software
88 rdf:type schema:DefinedTerm
89 N5485349df3fd425d8d7dac4bf642ac53 schema:name pubmed_id
90 schema:value 16925834
91 rdf:type schema:PropertyValue
92 N73bb751c1d9344ec9ba368a283798196 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Nucleotides
94 rdf:type schema:DefinedTerm
95 N7c9f613f27674f2d92e1dc4a39d0af2d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
96 schema:name Humans
97 rdf:type schema:DefinedTerm
98 N8aa7b66ecf6149d9801f1fcf7e915e24 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
99 schema:name RNA, Messenger
100 rdf:type schema:DefinedTerm
101 N90013f5211554243b7306821dcd57426 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
102 schema:name Genes
103 rdf:type schema:DefinedTerm
104 N97f0a1acafd64198a0f7f5fd40c334a8 rdf:first sg:person.01002567201.20
105 rdf:rest rdf:nil
106 N9a16e6e0322d4a7e886e22e7ecce7fa1 schema:issueNumber Suppl 1
107 rdf:type schema:PublicationIssue
108 N9c216a8577294a279da353ebef685b94 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Exons
110 rdf:type schema:DefinedTerm
111 Nafd126653cc94e7dab3773903ce43795 schema:volumeNumber 7
112 rdf:type schema:PublicationVolume
113 Nba7f1e715e5b4b55a8646c2332d55da5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name DNA, Complementary
115 rdf:type schema:DefinedTerm
116 Nbe751165bce94938a573a9448a185bc7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
117 schema:name Introns
118 rdf:type schema:DefinedTerm
119 Ndf6eecb717c74d1e977a93d8057e20c4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Genomics
121 rdf:type schema:DefinedTerm
122 Ne538f345de2f443f95e85478f880d27a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Sequence Analysis, RNA
124 rdf:type schema:DefinedTerm
125 Nf5a520b206ef4c1e9b02f9ca7827873f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Computational Biology
127 rdf:type schema:DefinedTerm
128 Nfe3ad44ccbc44895a504b09145e3d4dc rdf:first sg:person.0666340601.58
129 rdf:rest N97f0a1acafd64198a0f7f5fd40c334a8
130 Nff02b5c901c74fe6ab60def8958024a8 schema:name nlm_unique_id
131 schema:value 100960660
132 rdf:type schema:PropertyValue
133 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
134 schema:name Biological Sciences
135 rdf:type schema:DefinedTerm
136 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
137 schema:name Genetics
138 rdf:type schema:DefinedTerm
139 sg:journal.1023439 schema:issn 1465-6906
140 1474-760X
141 schema:name Genome Biology
142 rdf:type schema:Periodical
143 sg:person.01002567201.20 schema:affiliation https://www.grid.ac/institutes/grid.420086.8
144 schema:familyName Thierry-Mieg
145 schema:givenName Jean
146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01002567201.20
147 rdf:type schema:Person
148 sg:person.0666340601.58 schema:affiliation https://www.grid.ac/institutes/grid.420086.8
149 schema:familyName Thierry-Mieg
150 schema:givenName Danielle
151 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0666340601.58
152 rdf:type schema:Person
153 sg:pub.10.1038/85913 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002028191
154 https://doi.org/10.1038/85913
155 rdf:type schema:CreativeWork
156 sg:pub.10.1038/nature03001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013534924
157 https://doi.org/10.1038/nature03001
158 rdf:type schema:CreativeWork
159 sg:pub.10.1038/ng1285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018946050
160 https://doi.org/10.1038/ng1285
161 rdf:type schema:CreativeWork
162 sg:pub.10.1038/ng1429 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015685857
163 https://doi.org/10.1038/ng1429
164 rdf:type schema:CreativeWork
165 sg:pub.10.1038/nmeth0805-575 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020319965
166 https://doi.org/10.1038/nmeth0805-575
167 rdf:type schema:CreativeWork
168 sg:pub.10.1186/gb-2006-7-s1-s2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048969371
169 https://doi.org/10.1186/gb-2006-7-s1-s2
170 rdf:type schema:CreativeWork
171 https://app.dimensions.ai/details/publication/pub.1083300833 schema:CreativeWork
172 https://doi.org/10.1016/j.tig.2005.01.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024789565
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1016/s0248-4900(03)00033-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047504577
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1016/s0378-1119(02)01056-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028350454
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1038/sj.emboj.7601023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001779862
179 rdf:type schema:CreativeWork
180 https://doi.org/10.1074/jbc.m511265200 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036174700
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1093/embo-reports/kve085 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026461752
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1093/nar/gkj144 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005091941
185 rdf:type schema:CreativeWork
186 https://doi.org/10.1101/gr.2384604 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021287423
187 rdf:type schema:CreativeWork
188 https://doi.org/10.1101/gr.3729105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011381905
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1101/gr.4039406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033353829
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1126/science.1105136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031973383
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1126/science.1111443 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016370374
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1128/mcb.19.12.8505 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006841201
197 rdf:type schema:CreativeWork
198 https://doi.org/10.1128/mcb.9.11.5073 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039128892
199 rdf:type schema:CreativeWork
200 https://doi.org/10.1242/jcs.01701 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005027838
201 rdf:type schema:CreativeWork
202 https://doi.org/10.2174/138920306776359795 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069179117
203 rdf:type schema:CreativeWork
204 https://www.grid.ac/institutes/grid.420086.8 schema:alternateName National Institute of Arthritis and Musculoskeletal and Skin Diseases
205 schema:name National Center for Biotechnology Information, National Library of Medicine, NIH, 20894, Bethesda, MD, USA
206 rdf:type schema:Organization
 




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


...