High-quality genome (re)assembly using chromosomal contact data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Hervé Marie-Nelly, Martial Marbouty, Axel Cournac, Jean-François Flot, Gianni Liti, Dante Poggi Parodi, Sylvie Syan, Nancy Guillén, Antoine Margeot, Christophe Zimmer, Romain Koszul

ABSTRACT

Closing gaps in draft genome assemblies can be costly and time-consuming, and published genomes are therefore often left 'unfinished.' Here we show that genome-wide chromosome conformation capture (3C) data can be used to overcome these limitations, and present a computational approach rooted in polymer physics that determines the most likely genome structure using chromosomal contact data. This algorithm--named GRAAL--generates high-quality assemblies of genomes in which repeated and duplicated regions are accurately represented and offers a direct probabilistic interpretation of the computed structures. We first validated GRAAL on the reference genome of Saccharomyces cerevisiae, as well as other yeast isolates, where GRAAL recovered both known and unknown complex chromosomal structural variations. We then applied GRAAL to the finishing of the assembly of Trichoderma reesei and obtained a number of contigs congruent with the know karyotype of this species. Finally, we showed that GRAAL can accurately reconstruct human chromosomes from either fragments generated in silico or contigs obtained from de novo assembly. In all these applications, GRAAL compared favourably to recently published programmes implementing related approaches. More... »

PAGES

5695

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ncomms6695

DOI

http://dx.doi.org/10.1038/ncomms6695

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004047595

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25517223


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/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Algorithms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Chromosomes, Fungal", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Chromosomes, Human", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Contig Mapping", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genome", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "High-Throughput Nucleotide Sequencing", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Karyotype", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Statistical", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Saccharomyces cerevisiae", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sequence Analysis, DNA", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Trichoderma", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Sorbonne University", 
          "id": "https://www.grid.ac/institutes/grid.462844.8", 
          "name": [
            "Institut Pasteur, Department of Genomes and Genetics, Groupe R\u00e9gulation Spatiale des G\u00e9nomes, 75015 Paris, France", 
            "CNRS, UMR 3525, 75015 Paris, France", 
            "Institut Pasteur, Unit\u00e9 Imagerie et Mod\u00e9lisation, 75015 Paris, France", 
            "CNRS, URA 2582, 75015 Paris, France", 
            "Sorbonne Universit\u00e9s, UPMC Univ Paris06, IFD, 4 place Jussieu, 75252 Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Marie-Nelly", 
        "givenName": "Herv\u00e9", 
        "id": "sg:person.01325502670.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01325502670.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Institut Pasteur, Department of Genomes and Genetics, Groupe R\u00e9gulation Spatiale des G\u00e9nomes, 75015 Paris, France", 
            "CNRS, UMR 3525, 75015 Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Marbouty", 
        "givenName": "Martial", 
        "id": "sg:person.01273367770.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01273367770.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Institut Pasteur, Department of Genomes and Genetics, Groupe R\u00e9gulation Spatiale des G\u00e9nomes, 75015 Paris, France", 
            "CNRS, UMR 3525, 75015 Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cournac", 
        "givenName": "Axel", 
        "id": "sg:person.01157141370.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01157141370.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Max Planck Institute for Dynamics and Self Organization", 
          "id": "https://www.grid.ac/institutes/grid.419514.c", 
          "name": [
            "Max Planck Institute for Dynamics and Self-Organization, Group Biological Physics and Evolutionary Dynamics, Bunsenstr. 10, 37073 G\u00f6ttingen, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Flot", 
        "givenName": "Jean-Fran\u00e7ois", 
        "id": "sg:person.0661464674.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0661464674.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nice Sophia Antipolis University", 
          "id": "https://www.grid.ac/institutes/grid.10737.32", 
          "name": [
            "Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284\u2014INSERM U108, Universit\u00e9 de Nice Sophia Antipolis, 06107 Nice, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liti", 
        "givenName": "Gianni", 
        "id": "sg:person.01140234414.73", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140234414.73"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French Institute of Petroleum", 
          "id": "https://www.grid.ac/institutes/grid.13464.34", 
          "name": [
            "Sorbonne Universit\u00e9s, UPMC Univ Paris06, IFD, 4 place Jussieu, 75252 Paris, France", 
            "IFP Energies Nouvelles, 1 et 4 avenue de Bois-Pr\u00e9au, 92852 Rueil-Malmaison, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Parodi", 
        "givenName": "Dante Poggi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institut Pasteur", 
          "id": "https://www.grid.ac/institutes/grid.428999.7", 
          "name": [
            "Institut Pasteur, Unit\u00e9 Cell Biology of Parasitism, 75015 Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Syan", 
        "givenName": "Sylvie", 
        "id": "sg:person.0752163707.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752163707.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institut Pasteur", 
          "id": "https://www.grid.ac/institutes/grid.428999.7", 
          "name": [
            "Institut Pasteur, Unit\u00e9 Cell Biology of Parasitism, 75015 Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guill\u00e9n", 
        "givenName": "Nancy", 
        "id": "sg:person.01075103631.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01075103631.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French Institute of Petroleum", 
          "id": "https://www.grid.ac/institutes/grid.13464.34", 
          "name": [
            "IFP Energies Nouvelles, 1 et 4 avenue de Bois-Pr\u00e9au, 92852 Rueil-Malmaison, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Margeot", 
        "givenName": "Antoine", 
        "id": "sg:person.0623057603.65", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0623057603.65"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Institut Pasteur, Unit\u00e9 Imagerie et Mod\u00e9lisation, 75015 Paris, France", 
            "CNRS, URA 2582, 75015 Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zimmer", 
        "givenName": "Christophe", 
        "id": "sg:person.01032344365.82", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01032344365.82"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "Institut Pasteur, Department of Genomes and Genetics, Groupe R\u00e9gulation Spatiale des G\u00e9nomes, 75015 Paris, France", 
            "CNRS, UMR 3525, 75015 Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Koszul", 
        "givenName": "Romain", 
        "id": "sg:person.01104257515.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01104257515.27"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/1471-2164-13-436", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000529945", 
          "https://doi.org/10.1186/1471-2164-13-436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pgen.1003621", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002703662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00351657", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003208493", 
          "https://doi.org/10.1007/bf00351657"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1017351108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004253849"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2958", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004346662", 
          "https://doi.org/10.1038/nrg2958"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gad.1782209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005484326"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1923", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006541515", 
          "https://doi.org/10.1038/nmeth.1923"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cub.2012.07.069", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006855174"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1181369", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007401642"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1181369", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007401642"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt1403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008676346", 
          "https://doi.org/10.1038/nbt1403"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.2727", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009746211", 
          "https://doi.org/10.1038/nbt.2727"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1810", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010151067", 
          "https://doi.org/10.1038/nmeth.1810"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.129437.111", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010573540"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/mcb.4.11.2509", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010982843"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0968-0004(01)01978-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012092688"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature08973", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012207766", 
          "https://doi.org/10.1038/nature08973"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/sj.emboj.7600024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012705236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1527", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015617800", 
          "https://doi.org/10.1038/nmeth.1527"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1527", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015617800", 
          "https://doi.org/10.1038/nmeth.1527"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.1883", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015803168", 
          "https://doi.org/10.1038/nbt.1883"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btu162", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016068903"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/mcas.2010.936282", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017860195"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1067799", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021591890"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/yea.2991", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023430325"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/mcb.5.11.2894", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023752316"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.2425", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024094342", 
          "https://doi.org/10.1038/nbt.2425"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2012.01.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025469351"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ymeth.2012.11.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027083095"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ymeth.2012.11.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027083095"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2958.1992.tb01390.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029750354"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.micro.59.030804.121400", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031433282"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.micro.59.030804.121400", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031433282"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg3367", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032134076", 
          "https://doi.org/10.1038/nrg3367"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1138878", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032998331"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.2768", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035519327", 
          "https://doi.org/10.1038/nbt.2768"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/2047-217x-2-10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036067883", 
          "https://doi.org/10.1186/2047-217x-2-10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1112570109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037241633"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0034-4885/77/2/022601", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038371376"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.2478", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042175144", 
          "https://doi.org/10.1038/nbt.2478"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.168450.113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043064415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.131383.111", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044181786"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35013058", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047561279", 
          "https://doi.org/10.1038/35013058"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35013058", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047561279", 
          "https://doi.org/10.1038/35013058"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-294x.2011.05005.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048649936"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1204799109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050094503"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.parco.2011.09.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053544483"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2000.10473908", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058305669"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1099/mic.0.056424-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060395283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1110428", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062452044"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.274.5287.546", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062554574"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-12", 
    "datePublishedReg": "2014-12-01", 
    "description": "Closing gaps in draft genome assemblies can be costly and time-consuming, and published genomes are therefore often left 'unfinished.' Here we show that genome-wide chromosome conformation capture (3C) data can be used to overcome these limitations, and present a computational approach rooted in polymer physics that determines the most likely genome structure using chromosomal contact data. This algorithm--named GRAAL--generates high-quality assemblies of genomes in which repeated and duplicated regions are accurately represented and offers a direct probabilistic interpretation of the computed structures. We first validated GRAAL on the reference genome of Saccharomyces cerevisiae, as well as other yeast isolates, where GRAAL recovered both known and unknown complex chromosomal structural variations. We then applied GRAAL to the finishing of the assembly of Trichoderma reesei and obtained a number of contigs congruent with the know karyotype of this species. Finally, we showed that GRAAL can accurately reconstruct human chromosomes from either fragments generated in silico or contigs obtained from de novo assembly. In all these applications, GRAAL compared favourably to recently published programmes implementing related approaches.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/ncomms6695", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3786399", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.3793152", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1043282", 
        "issn": [
          "2041-1723"
        ], 
        "name": "Nature Communications", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "5"
      }
    ], 
    "name": "High-quality genome (re)assembly using chromosomal contact data", 
    "pagination": "5695", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "13491e9dc7a910377aa194db9287546ae1c0e3ec4d74ac7d47224aff17d369f7"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "25517223"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101528555"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/ncomms6695"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1004047595"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/ncomms6695", 
      "https://app.dimensions.ai/details/publication/pub.1004047595"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T21:25", 
    "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_8687_00000435.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/ncomms6695"
  }
]
 

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/ncomms6695'

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/ncomms6695'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/ncomms6695'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/ncomms6695'


 

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

366 TRIPLES      21 PREDICATES      87 URIs      33 LITERALS      21 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/ncomms6695 schema:about N01ede61792504c27b5a6662f6a21bf11
2 N037ca007edac43ffb8ad8ae33b00d4b9
3 N32a307deb7e448cd8c946839bcbe8654
4 N556e7d9816a14536b569a90b3f9632ba
5 N6946537ab86446bc8a0163b8c83bac2a
6 N8114b25afb934ea98c89cfd311f17226
7 N8e63998363d24bf6a9fcc3f483b45151
8 N90393903e64948d0856fe970b68596c3
9 N9af83f0523a84937aa2a61b0149da102
10 Na882eea0bc0348eb94470cee5e90c3cf
11 Nba40396d9841446783900eb881dde25e
12 Nfd23e80126354002b21acb218d3bf568
13 anzsrc-for:08
14 anzsrc-for:0801
15 schema:author Nfc66a51419fe475ea237358fb2cd0327
16 schema:citation sg:pub.10.1007/bf00351657
17 sg:pub.10.1038/35013058
18 sg:pub.10.1038/nature08973
19 sg:pub.10.1038/nbt.1883
20 sg:pub.10.1038/nbt.2425
21 sg:pub.10.1038/nbt.2478
22 sg:pub.10.1038/nbt.2727
23 sg:pub.10.1038/nbt.2768
24 sg:pub.10.1038/nbt1403
25 sg:pub.10.1038/nmeth.1527
26 sg:pub.10.1038/nmeth.1810
27 sg:pub.10.1038/nmeth.1923
28 sg:pub.10.1038/nrg2958
29 sg:pub.10.1038/nrg3367
30 sg:pub.10.1186/1471-2164-13-436
31 sg:pub.10.1186/2047-217x-2-10
32 https://doi.org/10.1002/yea.2991
33 https://doi.org/10.1016/j.cell.2012.01.010
34 https://doi.org/10.1016/j.cub.2012.07.069
35 https://doi.org/10.1016/j.parco.2011.09.001
36 https://doi.org/10.1016/j.ymeth.2012.11.005
37 https://doi.org/10.1016/s0968-0004(01)01978-8
38 https://doi.org/10.1038/sj.emboj.7600024
39 https://doi.org/10.1073/pnas.1017351108
40 https://doi.org/10.1073/pnas.1112570109
41 https://doi.org/10.1073/pnas.1204799109
42 https://doi.org/10.1080/01621459.2000.10473908
43 https://doi.org/10.1088/0034-4885/77/2/022601
44 https://doi.org/10.1093/bioinformatics/btu162
45 https://doi.org/10.1099/mic.0.056424-0
46 https://doi.org/10.1101/gad.1782209
47 https://doi.org/10.1101/gr.129437.111
48 https://doi.org/10.1101/gr.131383.111
49 https://doi.org/10.1101/gr.168450.113
50 https://doi.org/10.1109/mcas.2010.936282
51 https://doi.org/10.1111/j.1365-294x.2011.05005.x
52 https://doi.org/10.1111/j.1365-2958.1992.tb01390.x
53 https://doi.org/10.1126/science.1067799
54 https://doi.org/10.1126/science.1110428
55 https://doi.org/10.1126/science.1138878
56 https://doi.org/10.1126/science.1181369
57 https://doi.org/10.1126/science.274.5287.546
58 https://doi.org/10.1128/mcb.4.11.2509
59 https://doi.org/10.1128/mcb.5.11.2894
60 https://doi.org/10.1146/annurev.micro.59.030804.121400
61 https://doi.org/10.1371/journal.pgen.1003621
62 schema:datePublished 2014-12
63 schema:datePublishedReg 2014-12-01
64 schema:description Closing gaps in draft genome assemblies can be costly and time-consuming, and published genomes are therefore often left 'unfinished.' Here we show that genome-wide chromosome conformation capture (3C) data can be used to overcome these limitations, and present a computational approach rooted in polymer physics that determines the most likely genome structure using chromosomal contact data. This algorithm--named GRAAL--generates high-quality assemblies of genomes in which repeated and duplicated regions are accurately represented and offers a direct probabilistic interpretation of the computed structures. We first validated GRAAL on the reference genome of Saccharomyces cerevisiae, as well as other yeast isolates, where GRAAL recovered both known and unknown complex chromosomal structural variations. We then applied GRAAL to the finishing of the assembly of Trichoderma reesei and obtained a number of contigs congruent with the know karyotype of this species. Finally, we showed that GRAAL can accurately reconstruct human chromosomes from either fragments generated in silico or contigs obtained from de novo assembly. In all these applications, GRAAL compared favourably to recently published programmes implementing related approaches.
65 schema:genre research_article
66 schema:inLanguage en
67 schema:isAccessibleForFree true
68 schema:isPartOf N0106b07ba7ce42908373c34738deb3b9
69 Nb83d0d19ecaa4a889625d14ed0fabe84
70 sg:journal.1043282
71 schema:name High-quality genome (re)assembly using chromosomal contact data
72 schema:pagination 5695
73 schema:productId N0aaf517b65c44230a853ac03957b5cc8
74 N5715b120511d44669e7ba7b4c22c52c1
75 N7f668259d4264abf8e856b7275131282
76 N9d7857fee0ef477793416ec2fc17ce72
77 Nec5842d40bfe46ee80d574a22bbddec1
78 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004047595
79 https://doi.org/10.1038/ncomms6695
80 schema:sdDatePublished 2019-04-10T21:25
81 schema:sdLicense https://scigraph.springernature.com/explorer/license/
82 schema:sdPublisher N7dd19020dfee4889bec053ddc009cfef
83 schema:url https://www.nature.com/articles/ncomms6695
84 sgo:license sg:explorer/license/
85 sgo:sdDataset articles
86 rdf:type schema:ScholarlyArticle
87 N0106b07ba7ce42908373c34738deb3b9 schema:issueNumber 1
88 rdf:type schema:PublicationIssue
89 N01ede61792504c27b5a6662f6a21bf11 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name High-Throughput Nucleotide Sequencing
91 rdf:type schema:DefinedTerm
92 N037ca007edac43ffb8ad8ae33b00d4b9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Karyotype
94 rdf:type schema:DefinedTerm
95 N0aaf517b65c44230a853ac03957b5cc8 schema:name dimensions_id
96 schema:value pub.1004047595
97 rdf:type schema:PropertyValue
98 N32a307deb7e448cd8c946839bcbe8654 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
99 schema:name Models, Statistical
100 rdf:type schema:DefinedTerm
101 N340ed96bda0e4b868d14c4d5dccf5128 rdf:first N44edd5c4ad404d91903a3724674fec91
102 rdf:rest Naa28c7cc13ab4fe1acdbb383045bc403
103 N44edd5c4ad404d91903a3724674fec91 schema:affiliation https://www.grid.ac/institutes/grid.13464.34
104 schema:familyName Parodi
105 schema:givenName Dante Poggi
106 rdf:type schema:Person
107 N556e7d9816a14536b569a90b3f9632ba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
108 schema:name Humans
109 rdf:type schema:DefinedTerm
110 N5715b120511d44669e7ba7b4c22c52c1 schema:name readcube_id
111 schema:value 13491e9dc7a910377aa194db9287546ae1c0e3ec4d74ac7d47224aff17d369f7
112 rdf:type schema:PropertyValue
113 N682117be2e8b47389deecfa8994d0204 rdf:first sg:person.01157141370.70
114 rdf:rest N9e6b08d0cdb540d5998227cdbf75fe5d
115 N6946537ab86446bc8a0163b8c83bac2a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
116 schema:name Trichoderma
117 rdf:type schema:DefinedTerm
118 N76e4a8745b454e8089dc838674ff49d6 rdf:first sg:person.01032344365.82
119 rdf:rest Nd929d2ab4d1f47ee94b5fb73f3344431
120 N7dd19020dfee4889bec053ddc009cfef schema:name Springer Nature - SN SciGraph project
121 rdf:type schema:Organization
122 N7f668259d4264abf8e856b7275131282 schema:name doi
123 schema:value 10.1038/ncomms6695
124 rdf:type schema:PropertyValue
125 N8114b25afb934ea98c89cfd311f17226 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Genome
127 rdf:type schema:DefinedTerm
128 N8d8e861983d5441383729a2d196b12f2 rdf:first sg:person.01075103631.03
129 rdf:rest Nae1766a5378c49519070dd530236977f
130 N8e63998363d24bf6a9fcc3f483b45151 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Chromosomes, Fungal
132 rdf:type schema:DefinedTerm
133 N90393903e64948d0856fe970b68596c3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Sequence Analysis, DNA
135 rdf:type schema:DefinedTerm
136 N9792d9e07d604efc9873990eaa2f9aad rdf:first sg:person.01140234414.73
137 rdf:rest N340ed96bda0e4b868d14c4d5dccf5128
138 N9af83f0523a84937aa2a61b0149da102 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Contig Mapping
140 rdf:type schema:DefinedTerm
141 N9d7857fee0ef477793416ec2fc17ce72 schema:name pubmed_id
142 schema:value 25517223
143 rdf:type schema:PropertyValue
144 N9e6b08d0cdb540d5998227cdbf75fe5d rdf:first sg:person.0661464674.80
145 rdf:rest N9792d9e07d604efc9873990eaa2f9aad
146 Na882eea0bc0348eb94470cee5e90c3cf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
147 schema:name Chromosomes, Human
148 rdf:type schema:DefinedTerm
149 Naa28c7cc13ab4fe1acdbb383045bc403 rdf:first sg:person.0752163707.22
150 rdf:rest N8d8e861983d5441383729a2d196b12f2
151 Nae1766a5378c49519070dd530236977f rdf:first sg:person.0623057603.65
152 rdf:rest N76e4a8745b454e8089dc838674ff49d6
153 Nb83d0d19ecaa4a889625d14ed0fabe84 schema:volumeNumber 5
154 rdf:type schema:PublicationVolume
155 Nba40396d9841446783900eb881dde25e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
156 schema:name Saccharomyces cerevisiae
157 rdf:type schema:DefinedTerm
158 Nd929d2ab4d1f47ee94b5fb73f3344431 rdf:first sg:person.01104257515.27
159 rdf:rest rdf:nil
160 Ne5073849db10495ea6056b9310017897 rdf:first sg:person.01273367770.62
161 rdf:rest N682117be2e8b47389deecfa8994d0204
162 Nec5842d40bfe46ee80d574a22bbddec1 schema:name nlm_unique_id
163 schema:value 101528555
164 rdf:type schema:PropertyValue
165 Nfc66a51419fe475ea237358fb2cd0327 rdf:first sg:person.01325502670.52
166 rdf:rest Ne5073849db10495ea6056b9310017897
167 Nfd23e80126354002b21acb218d3bf568 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
168 schema:name Algorithms
169 rdf:type schema:DefinedTerm
170 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
171 schema:name Information and Computing Sciences
172 rdf:type schema:DefinedTerm
173 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
174 schema:name Artificial Intelligence and Image Processing
175 rdf:type schema:DefinedTerm
176 sg:grant.3786399 http://pending.schema.org/fundedItem sg:pub.10.1038/ncomms6695
177 rdf:type schema:MonetaryGrant
178 sg:grant.3793152 http://pending.schema.org/fundedItem sg:pub.10.1038/ncomms6695
179 rdf:type schema:MonetaryGrant
180 sg:journal.1043282 schema:issn 2041-1723
181 schema:name Nature Communications
182 rdf:type schema:Periodical
183 sg:person.01032344365.82 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
184 schema:familyName Zimmer
185 schema:givenName Christophe
186 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01032344365.82
187 rdf:type schema:Person
188 sg:person.01075103631.03 schema:affiliation https://www.grid.ac/institutes/grid.428999.7
189 schema:familyName Guillén
190 schema:givenName Nancy
191 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01075103631.03
192 rdf:type schema:Person
193 sg:person.01104257515.27 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
194 schema:familyName Koszul
195 schema:givenName Romain
196 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01104257515.27
197 rdf:type schema:Person
198 sg:person.01140234414.73 schema:affiliation https://www.grid.ac/institutes/grid.10737.32
199 schema:familyName Liti
200 schema:givenName Gianni
201 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140234414.73
202 rdf:type schema:Person
203 sg:person.01157141370.70 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
204 schema:familyName Cournac
205 schema:givenName Axel
206 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01157141370.70
207 rdf:type schema:Person
208 sg:person.01273367770.62 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
209 schema:familyName Marbouty
210 schema:givenName Martial
211 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01273367770.62
212 rdf:type schema:Person
213 sg:person.01325502670.52 schema:affiliation https://www.grid.ac/institutes/grid.462844.8
214 schema:familyName Marie-Nelly
215 schema:givenName Hervé
216 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01325502670.52
217 rdf:type schema:Person
218 sg:person.0623057603.65 schema:affiliation https://www.grid.ac/institutes/grid.13464.34
219 schema:familyName Margeot
220 schema:givenName Antoine
221 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0623057603.65
222 rdf:type schema:Person
223 sg:person.0661464674.80 schema:affiliation https://www.grid.ac/institutes/grid.419514.c
224 schema:familyName Flot
225 schema:givenName Jean-François
226 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0661464674.80
227 rdf:type schema:Person
228 sg:person.0752163707.22 schema:affiliation https://www.grid.ac/institutes/grid.428999.7
229 schema:familyName Syan
230 schema:givenName Sylvie
231 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752163707.22
232 rdf:type schema:Person
233 sg:pub.10.1007/bf00351657 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003208493
234 https://doi.org/10.1007/bf00351657
235 rdf:type schema:CreativeWork
236 sg:pub.10.1038/35013058 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047561279
237 https://doi.org/10.1038/35013058
238 rdf:type schema:CreativeWork
239 sg:pub.10.1038/nature08973 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012207766
240 https://doi.org/10.1038/nature08973
241 rdf:type schema:CreativeWork
242 sg:pub.10.1038/nbt.1883 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015803168
243 https://doi.org/10.1038/nbt.1883
244 rdf:type schema:CreativeWork
245 sg:pub.10.1038/nbt.2425 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024094342
246 https://doi.org/10.1038/nbt.2425
247 rdf:type schema:CreativeWork
248 sg:pub.10.1038/nbt.2478 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042175144
249 https://doi.org/10.1038/nbt.2478
250 rdf:type schema:CreativeWork
251 sg:pub.10.1038/nbt.2727 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009746211
252 https://doi.org/10.1038/nbt.2727
253 rdf:type schema:CreativeWork
254 sg:pub.10.1038/nbt.2768 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035519327
255 https://doi.org/10.1038/nbt.2768
256 rdf:type schema:CreativeWork
257 sg:pub.10.1038/nbt1403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008676346
258 https://doi.org/10.1038/nbt1403
259 rdf:type schema:CreativeWork
260 sg:pub.10.1038/nmeth.1527 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015617800
261 https://doi.org/10.1038/nmeth.1527
262 rdf:type schema:CreativeWork
263 sg:pub.10.1038/nmeth.1810 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010151067
264 https://doi.org/10.1038/nmeth.1810
265 rdf:type schema:CreativeWork
266 sg:pub.10.1038/nmeth.1923 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006541515
267 https://doi.org/10.1038/nmeth.1923
268 rdf:type schema:CreativeWork
269 sg:pub.10.1038/nrg2958 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004346662
270 https://doi.org/10.1038/nrg2958
271 rdf:type schema:CreativeWork
272 sg:pub.10.1038/nrg3367 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032134076
273 https://doi.org/10.1038/nrg3367
274 rdf:type schema:CreativeWork
275 sg:pub.10.1186/1471-2164-13-436 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000529945
276 https://doi.org/10.1186/1471-2164-13-436
277 rdf:type schema:CreativeWork
278 sg:pub.10.1186/2047-217x-2-10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036067883
279 https://doi.org/10.1186/2047-217x-2-10
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1002/yea.2991 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023430325
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1016/j.cell.2012.01.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025469351
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1016/j.cub.2012.07.069 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006855174
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1016/j.parco.2011.09.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053544483
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1016/j.ymeth.2012.11.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027083095
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1016/s0968-0004(01)01978-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012092688
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1038/sj.emboj.7600024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012705236
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1073/pnas.1017351108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004253849
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1073/pnas.1112570109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037241633
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1073/pnas.1204799109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050094503
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1080/01621459.2000.10473908 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058305669
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1088/0034-4885/77/2/022601 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038371376
304 rdf:type schema:CreativeWork
305 https://doi.org/10.1093/bioinformatics/btu162 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016068903
306 rdf:type schema:CreativeWork
307 https://doi.org/10.1099/mic.0.056424-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060395283
308 rdf:type schema:CreativeWork
309 https://doi.org/10.1101/gad.1782209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005484326
310 rdf:type schema:CreativeWork
311 https://doi.org/10.1101/gr.129437.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010573540
312 rdf:type schema:CreativeWork
313 https://doi.org/10.1101/gr.131383.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044181786
314 rdf:type schema:CreativeWork
315 https://doi.org/10.1101/gr.168450.113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043064415
316 rdf:type schema:CreativeWork
317 https://doi.org/10.1109/mcas.2010.936282 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017860195
318 rdf:type schema:CreativeWork
319 https://doi.org/10.1111/j.1365-294x.2011.05005.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1048649936
320 rdf:type schema:CreativeWork
321 https://doi.org/10.1111/j.1365-2958.1992.tb01390.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1029750354
322 rdf:type schema:CreativeWork
323 https://doi.org/10.1126/science.1067799 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021591890
324 rdf:type schema:CreativeWork
325 https://doi.org/10.1126/science.1110428 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062452044
326 rdf:type schema:CreativeWork
327 https://doi.org/10.1126/science.1138878 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032998331
328 rdf:type schema:CreativeWork
329 https://doi.org/10.1126/science.1181369 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007401642
330 rdf:type schema:CreativeWork
331 https://doi.org/10.1126/science.274.5287.546 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062554574
332 rdf:type schema:CreativeWork
333 https://doi.org/10.1128/mcb.4.11.2509 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010982843
334 rdf:type schema:CreativeWork
335 https://doi.org/10.1128/mcb.5.11.2894 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023752316
336 rdf:type schema:CreativeWork
337 https://doi.org/10.1146/annurev.micro.59.030804.121400 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031433282
338 rdf:type schema:CreativeWork
339 https://doi.org/10.1371/journal.pgen.1003621 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002703662
340 rdf:type schema:CreativeWork
341 https://www.grid.ac/institutes/grid.10737.32 schema:alternateName Nice Sophia Antipolis University
342 schema:name Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284—INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France
343 rdf:type schema:Organization
344 https://www.grid.ac/institutes/grid.13464.34 schema:alternateName French Institute of Petroleum
345 schema:name IFP Energies Nouvelles, 1 et 4 avenue de Bois-Préau, 92852 Rueil-Malmaison, France
346 Sorbonne Universités, UPMC Univ Paris06, IFD, 4 place Jussieu, 75252 Paris, France
347 rdf:type schema:Organization
348 https://www.grid.ac/institutes/grid.419514.c schema:alternateName Max Planck Institute for Dynamics and Self Organization
349 schema:name Max Planck Institute for Dynamics and Self-Organization, Group Biological Physics and Evolutionary Dynamics, Bunsenstr. 10, 37073 Göttingen, Germany
350 rdf:type schema:Organization
351 https://www.grid.ac/institutes/grid.428999.7 schema:alternateName Institut Pasteur
352 schema:name Institut Pasteur, Unité Cell Biology of Parasitism, 75015 Paris, France
353 rdf:type schema:Organization
354 https://www.grid.ac/institutes/grid.4444.0 schema:alternateName French National Centre for Scientific Research
355 schema:name CNRS, UMR 3525, 75015 Paris, France
356 CNRS, URA 2582, 75015 Paris, France
357 Institut Pasteur, Department of Genomes and Genetics, Groupe Régulation Spatiale des Génomes, 75015 Paris, France
358 Institut Pasteur, Unité Imagerie et Modélisation, 75015 Paris, France
359 rdf:type schema:Organization
360 https://www.grid.ac/institutes/grid.462844.8 schema:alternateName Sorbonne University
361 schema:name CNRS, UMR 3525, 75015 Paris, France
362 CNRS, URA 2582, 75015 Paris, France
363 Institut Pasteur, Department of Genomes and Genetics, Groupe Régulation Spatiale des Génomes, 75015 Paris, France
364 Institut Pasteur, Unité Imagerie et Modélisation, 75015 Paris, France
365 Sorbonne Universités, UPMC Univ Paris06, IFD, 4 place Jussieu, 75252 Paris, France
366 rdf:type schema:Organization
 




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


...