Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-05

AUTHORS

Michal Rabani, Joshua Z Levin, Lin Fan, Xian Adiconis, Raktima Raychowdhury, Manuel Garber, Andreas Gnirke, Chad Nusbaum, Nir Hacohen, Nir Friedman, Ido Amit, Aviv Regev

ABSTRACT

Cellular RNA levels are determined by the interplay of RNA production, processing and degradation. However, because most studies of RNA regulation do not distinguish the separate contributions of these processes, little is known about how they are temporally integrated. Here we combine metabolic labeling of RNA at high temporal resolution with advanced RNA quantification and computational modeling to estimate RNA transcription and degradation rates during the response of mouse dendritic cells to lipopolysaccharide. We find that changes in transcription rates determine the majority of temporal changes in RNA levels, but that changes in degradation rates are important for shaping sharp 'peaked' responses. We used sequencing of the newly transcribed RNA population to estimate temporally constant RNA processing and degradation rates genome wide. Degradation rates vary significantly between genes and contribute to the observed differences in the dynamic response. Certain transcripts, including those encoding cytokines and transcription factors, mature faster. Our study provides a quantitative approach to study the integrative process of RNA regulation. More... »

PAGES

436

References to SciGraph publications

  • 2009-03. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome in GENOME BIOLOGY
  • 2005-12. Control of gene expression during T cell activation: alternate regulation of mRNA transcription and mRNA stability in BMC GENOMICS
  • 2002-06. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes in GENOME BIOLOGY
  • 2008-11. Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network in NATURE BIOTECHNOLOGY
  • 2008-07. Mapping and quantifying mammalian transcriptomes by RNA-Seq in NATURE METHODS
  • 2010-12. Major role for mRNA stability in shaping the kinetics of gene induction in BMC GENOMICS
  • 2008-03. Direct multiplexed measurement of gene expression with color-coded probe pairs in NATURE BIOTECHNOLOGY
  • 2009-03. The stability of mRNA influences the temporal order of the induction of genes encoding inflammatory molecules in NATURE IMMUNOLOGY
  • 2010-05. Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs in NATURE BIOTECHNOLOGY
  • 2005-02. Biosynthetic labeling of RNA with uracil phosphoribosyltransferase allows cell-specific microarray analysis of mRNA synthesis and decay in NATURE BIOTECHNOLOGY
  • 2007-04. A module of negative feedback regulators defines growth factor signaling in NATURE GENETICS
  • 2008-01. Predicting expression patterns from regulatory sequence in Drosophila segmentation in NATURE
  • 2010-09. Comprehensive comparative analysis of strand-specific RNA sequencing methods in NATURE METHODS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nbt.1861

    DOI

    http://dx.doi.org/10.1038/nbt.1861

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1042484997

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/21516085


    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": "Animals", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Biotinylation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cells, Cultured", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Computational Biology", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Dendritic Cells", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Down-Regulation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genetic Association Studies", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Lipopolysaccharides", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Mice", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Mice, Inbred C57BL", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Models, Molecular", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA Polymerase II", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA, Messenger", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Analysis, RNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Transcription Factors", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Transcription, Genetic", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Up-Regulation", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Massachusetts Institute of Technology", 
              "id": "https://www.grid.ac/institutes/grid.116068.8", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.", 
                "Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rabani", 
            "givenName": "Michal", 
            "id": "sg:person.01076324365.97", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01076324365.97"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Levin", 
            "givenName": "Joshua Z", 
            "id": "sg:person.01222432021.01", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01222432021.01"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fan", 
            "givenName": "Lin", 
            "id": "sg:person.0650451313.47", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650451313.47"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Adiconis", 
            "givenName": "Xian", 
            "id": "sg:person.01000014215.36", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000014215.36"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Raychowdhury", 
            "givenName": "Raktima", 
            "id": "sg:person.01243646203.36", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01243646203.36"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Garber", 
            "givenName": "Manuel", 
            "id": "sg:person.01213005106.80", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213005106.80"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Gnirke", 
            "givenName": "Andreas", 
            "id": "sg:person.0645200471.91", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645200471.91"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Nusbaum", 
            "givenName": "Chad", 
            "id": "sg:person.01170225154.35", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01170225154.35"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hacohen", 
            "givenName": "Nir", 
            "id": "sg:person.0631561714.29", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0631561714.29"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hebrew University of Jerusalem", 
              "id": "https://www.grid.ac/institutes/grid.9619.7", 
              "name": [
                "School of Computer Science, Hebrew University, Jerusalem, Israel.", 
                "Institute of Life Sciences, Hebrew University, Jerusalem, Israel."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Friedman", 
            "givenName": "Nir", 
            "id": "sg:person.01113613366.14", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113613366.14"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Broad Institute", 
              "id": "https://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Amit", 
            "givenName": "Ido", 
            "id": "sg:person.01330120620.44", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01330120620.44"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Massachusetts Institute of Technology", 
              "id": "https://www.grid.ac/institutes/grid.116068.8", 
              "name": [
                "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.", 
                "Howard Hughes Medical Institute, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Regev", 
            "givenName": "Aviv", 
            "id": "sg:person.01311753732.26", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01311753732.26"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1186/1471-2164-6-75", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000774804", 
              "https://doi.org/10.1186/1471-2164-6-75"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1061", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005901943", 
              "https://doi.org/10.1038/nbt1061"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1061", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005901943", 
              "https://doi.org/10.1038/nbt1061"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/mcb.17.2.809", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006049550"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb.2008.59", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006941967"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb.2008.59", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006941967"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkl842", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008035809"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0092-8674(01)00449-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008090278"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.092538799", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009364821"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb.2010.38", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010018471"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb.2010.38", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010018471"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp120", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012425816"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1162228", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013963804"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1162228", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013963804"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/yea.1548", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014770530"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkf682", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016001493"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb.2009.84", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016953373"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb.2009.84", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016953373"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb.2009.84", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016953373"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkl164", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019792439"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1491", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019899367", 
              "https://doi.org/10.1038/nmeth.1491"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1491", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019899367", 
              "https://doi.org/10.1038/nmeth.1491"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/mcb.00945-06", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023813666"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.1633", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025339324", 
              "https://doi.org/10.1038/nbt.1633"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ni.1699", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025578738", 
              "https://doi.org/10.1038/ni.1699"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1039/b911233b", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028841108"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1039/b911233b", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028841108"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1987", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032102166", 
              "https://doi.org/10.1038/ng1987"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkn766", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032292161"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.molcel.2004.06.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035947017"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0506580102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037705714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0506580102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037705714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkp939", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038538216"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkp939", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038538216"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ygeno.2006.03.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038813539"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2002-3-7-research0034", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039751959", 
              "https://doi.org/10.1186/gb-2002-3-7-research0034"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0610439104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040471829"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkp542", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042357646"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0092-8674(94)90221-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042602817"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature06496", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043696128", 
              "https://doi.org/10.1038/nature06496"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-11-259", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044029433", 
              "https://doi.org/10.1186/1471-2164-11-259"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1179050", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044210053"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1179050", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044210053"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045381177", 
              "https://doi.org/10.1038/nmeth.1226"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.1499", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046058321", 
              "https://doi.org/10.1038/nbt.1499"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pcbi.1000021", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046266506"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1261/rna.1136108", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047586134"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2009-10-3-r25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049583368", 
              "https://doi.org/10.1186/gb-2009-10-3-r25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bth941", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050276898"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkm929", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051689742"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb4100115", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052922326"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1038/msb4100115", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052922326"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1385", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053259870", 
              "https://doi.org/10.1038/nbt1385"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/s1355838299981190", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1054923946"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1089/cmb.2008.13tt", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059245763"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1174062", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062460150"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.281.5379.1001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062562056"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1137/s1052623496303470", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062883551"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1214/aoms/1177732360", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064402573"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1074814991", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077587903", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1171347", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077935333"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2011-05", 
        "datePublishedReg": "2011-05-01", 
        "description": "Cellular RNA levels are determined by the interplay of RNA production, processing and degradation. However, because most studies of RNA regulation do not distinguish the separate contributions of these processes, little is known about how they are temporally integrated. Here we combine metabolic labeling of RNA at high temporal resolution with advanced RNA quantification and computational modeling to estimate RNA transcription and degradation rates during the response of mouse dendritic cells to lipopolysaccharide. We find that changes in transcription rates determine the majority of temporal changes in RNA levels, but that changes in degradation rates are important for shaping sharp 'peaked' responses. We used sequencing of the newly transcribed RNA population to estimate temporally constant RNA processing and degradation rates genome wide. Degradation rates vary significantly between genes and contribute to the observed differences in the dynamic response. Certain transcripts, including those encoding cytokines and transcription factors, mature faster. Our study provides a quantitative approach to study the integrative process of RNA regulation.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1038/nbt.1861", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2355082", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2698981", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2675020", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2355252", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1115214", 
            "issn": [
              "1087-0156", 
              "1546-1696"
            ], 
            "name": "Nature Biotechnology", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "5", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "29"
          }
        ], 
        "name": "Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells", 
        "pagination": "436", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "ca5f9b0c62ece75088a51a949b08d71491f54b58297852b4f0bf8f612d07f71f"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "21516085"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "9604648"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/nbt.1861"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1042484997"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/nbt.1861", 
          "https://app.dimensions.ai/details/publication/pub.1042484997"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T01:48", 
        "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_8700_00000436.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://www.nature.com/articles/nbt.1861"
      }
    ]
     

    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/nbt.1861'

    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/nbt.1861'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nbt.1861'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nbt.1861'


     

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

    400 TRIPLES      21 PREDICATES      98 URIs      40 LITERALS      28 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/nbt.1861 schema:about N0154824a4c0c4017b3270ce73b81b14c
    2 N0851be2fb71d486085ddf8858bfb446e
    3 N25cbaf0a5b8d46b881851e86db9488cd
    4 N3f041285349640dcb3f38fb6c3fdc0fb
    5 N4c64cfe33310426ca963b2f691905572
    6 N8723d6b94a194eb597fbdee68d11ab10
    7 N91d32f3f31b043b58dd0d0a1de64a2f9
    8 Na3f3e1366f254ce9a165246ea1d09c6f
    9 Na62eb551d5ab4535bd8bd3feeb84ef91
    10 Na69e74b4c8a74e5687d5140002370936
    11 Na7b151b6e2c64759af3d4a773c1095b0
    12 Nb295ea8120264067b09d93ce9a4931f6
    13 Nb7153b4338684edea30341d394bd2355
    14 Nb9dbfdb2284d425f884340591f39d057
    15 Ndc6bf994cf2744cb90b0c12597583d2c
    16 Ne4f7ad52b8d4444997e14a8290dec0ec
    17 Nea99d0bb59f0478699875fa5c5384a59
    18 Nfa81b64e07234372aa080075f3077569
    19 Nfd4043cb3e674f35a888515480550b0d
    20 anzsrc-for:06
    21 anzsrc-for:0604
    22 schema:author N081b1b7537804c3cbc67b1a777831e89
    23 schema:citation sg:pub.10.1038/nature06496
    24 sg:pub.10.1038/nbt.1499
    25 sg:pub.10.1038/nbt.1633
    26 sg:pub.10.1038/nbt1061
    27 sg:pub.10.1038/nbt1385
    28 sg:pub.10.1038/ng1987
    29 sg:pub.10.1038/ni.1699
    30 sg:pub.10.1038/nmeth.1226
    31 sg:pub.10.1038/nmeth.1491
    32 sg:pub.10.1186/1471-2164-11-259
    33 sg:pub.10.1186/1471-2164-6-75
    34 sg:pub.10.1186/gb-2002-3-7-research0034
    35 sg:pub.10.1186/gb-2009-10-3-r25
    36 https://app.dimensions.ai/details/publication/pub.1074814991
    37 https://app.dimensions.ai/details/publication/pub.1077587903
    38 https://doi.org/10.1002/yea.1548
    39 https://doi.org/10.1016/0092-8674(94)90221-6
    40 https://doi.org/10.1016/j.molcel.2004.06.004
    41 https://doi.org/10.1016/j.ygeno.2006.03.022
    42 https://doi.org/10.1016/s0092-8674(01)00449-4
    43 https://doi.org/10.1017/s1355838299981190
    44 https://doi.org/10.1038/msb.2008.59
    45 https://doi.org/10.1038/msb.2009.84
    46 https://doi.org/10.1038/msb.2010.38
    47 https://doi.org/10.1038/msb4100115
    48 https://doi.org/10.1039/b911233b
    49 https://doi.org/10.1073/pnas.0506580102
    50 https://doi.org/10.1073/pnas.0610439104
    51 https://doi.org/10.1073/pnas.092538799
    52 https://doi.org/10.1089/cmb.2008.13tt
    53 https://doi.org/10.1093/bioinformatics/bth941
    54 https://doi.org/10.1093/bioinformatics/btp120
    55 https://doi.org/10.1093/nar/gkf682
    56 https://doi.org/10.1093/nar/gkl164
    57 https://doi.org/10.1093/nar/gkl842
    58 https://doi.org/10.1093/nar/gkm929
    59 https://doi.org/10.1093/nar/gkn766
    60 https://doi.org/10.1093/nar/gkp542
    61 https://doi.org/10.1093/nar/gkp939
    62 https://doi.org/10.1126/science.1162228
    63 https://doi.org/10.1126/science.1171347
    64 https://doi.org/10.1126/science.1174062
    65 https://doi.org/10.1126/science.1179050
    66 https://doi.org/10.1126/science.281.5379.1001
    67 https://doi.org/10.1128/mcb.00945-06
    68 https://doi.org/10.1128/mcb.17.2.809
    69 https://doi.org/10.1137/s1052623496303470
    70 https://doi.org/10.1214/aoms/1177732360
    71 https://doi.org/10.1261/rna.1136108
    72 https://doi.org/10.1371/journal.pcbi.1000021
    73 schema:datePublished 2011-05
    74 schema:datePublishedReg 2011-05-01
    75 schema:description Cellular RNA levels are determined by the interplay of RNA production, processing and degradation. However, because most studies of RNA regulation do not distinguish the separate contributions of these processes, little is known about how they are temporally integrated. Here we combine metabolic labeling of RNA at high temporal resolution with advanced RNA quantification and computational modeling to estimate RNA transcription and degradation rates during the response of mouse dendritic cells to lipopolysaccharide. We find that changes in transcription rates determine the majority of temporal changes in RNA levels, but that changes in degradation rates are important for shaping sharp 'peaked' responses. We used sequencing of the newly transcribed RNA population to estimate temporally constant RNA processing and degradation rates genome wide. Degradation rates vary significantly between genes and contribute to the observed differences in the dynamic response. Certain transcripts, including those encoding cytokines and transcription factors, mature faster. Our study provides a quantitative approach to study the integrative process of RNA regulation.
    76 schema:genre research_article
    77 schema:inLanguage en
    78 schema:isAccessibleForFree true
    79 schema:isPartOf Nc87b9028c79c4755ab14a4753795639a
    80 Ne347b8331bd44701929b993e72727294
    81 sg:journal.1115214
    82 schema:name Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells
    83 schema:pagination 436
    84 schema:productId N1a7784f39e2e42cdad471e690ff90864
    85 N2fd13287b52e4ecfb632050352392c2e
    86 N48d5733c55a94ff08ae7c44944d25e56
    87 N59083408c3024d6783470274d0fb6e36
    88 Ne5a1d6a728174613bc78d055fb5c5adf
    89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042484997
    90 https://doi.org/10.1038/nbt.1861
    91 schema:sdDatePublished 2019-04-11T01:48
    92 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    93 schema:sdPublisher N9f29e6303ebe40e28511dbd40dcc76d9
    94 schema:url https://www.nature.com/articles/nbt.1861
    95 sgo:license sg:explorer/license/
    96 sgo:sdDataset articles
    97 rdf:type schema:ScholarlyArticle
    98 N0154824a4c0c4017b3270ce73b81b14c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    99 schema:name Biotinylation
    100 rdf:type schema:DefinedTerm
    101 N081b1b7537804c3cbc67b1a777831e89 rdf:first sg:person.01076324365.97
    102 rdf:rest Nd589ebed30a7404b8b6f0e393d08944b
    103 N0851be2fb71d486085ddf8858bfb446e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    104 schema:name Down-Regulation
    105 rdf:type schema:DefinedTerm
    106 N0c5e16678f90497f98fd575e1dbcfde5 rdf:first sg:person.01330120620.44
    107 rdf:rest N6c4e626e99e249c9be9578af6b2651a9
    108 N1a7784f39e2e42cdad471e690ff90864 schema:name pubmed_id
    109 schema:value 21516085
    110 rdf:type schema:PropertyValue
    111 N25cbaf0a5b8d46b881851e86db9488cd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    112 schema:name Lipopolysaccharides
    113 rdf:type schema:DefinedTerm
    114 N2fd13287b52e4ecfb632050352392c2e schema:name readcube_id
    115 schema:value ca5f9b0c62ece75088a51a949b08d71491f54b58297852b4f0bf8f612d07f71f
    116 rdf:type schema:PropertyValue
    117 N3f041285349640dcb3f38fb6c3fdc0fb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    118 schema:name Computational Biology
    119 rdf:type schema:DefinedTerm
    120 N486097155db9438f943340e0a864b804 rdf:first sg:person.01000014215.36
    121 rdf:rest Nd2089cebaee848e4aa34667bb68c9f38
    122 N48d5733c55a94ff08ae7c44944d25e56 schema:name doi
    123 schema:value 10.1038/nbt.1861
    124 rdf:type schema:PropertyValue
    125 N4c64cfe33310426ca963b2f691905572 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    126 schema:name Animals
    127 rdf:type schema:DefinedTerm
    128 N4f42d74a7c454026a5db9b09db97d7e8 rdf:first sg:person.01213005106.80
    129 rdf:rest Nf111730a602d4fb4a67ee9f7f6b74acb
    130 N545a498765764fec87a6641179b8c8eb rdf:first sg:person.0631561714.29
    131 rdf:rest Na424763e52294b438f2a3cc2b9031678
    132 N59083408c3024d6783470274d0fb6e36 schema:name dimensions_id
    133 schema:value pub.1042484997
    134 rdf:type schema:PropertyValue
    135 N6c4e626e99e249c9be9578af6b2651a9 rdf:first sg:person.01311753732.26
    136 rdf:rest rdf:nil
    137 N76069f599ec14f0c8851d4984c23aa36 rdf:first sg:person.0650451313.47
    138 rdf:rest N486097155db9438f943340e0a864b804
    139 N8723d6b94a194eb597fbdee68d11ab10 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    140 schema:name Mice, Inbred C57BL
    141 rdf:type schema:DefinedTerm
    142 N91d32f3f31b043b58dd0d0a1de64a2f9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    143 schema:name RNA, Messenger
    144 rdf:type schema:DefinedTerm
    145 N9f29e6303ebe40e28511dbd40dcc76d9 schema:name Springer Nature - SN SciGraph project
    146 rdf:type schema:Organization
    147 Na3f3e1366f254ce9a165246ea1d09c6f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    148 schema:name Up-Regulation
    149 rdf:type schema:DefinedTerm
    150 Na424763e52294b438f2a3cc2b9031678 rdf:first sg:person.01113613366.14
    151 rdf:rest N0c5e16678f90497f98fd575e1dbcfde5
    152 Na62eb551d5ab4535bd8bd3feeb84ef91 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    153 schema:name Models, Molecular
    154 rdf:type schema:DefinedTerm
    155 Na69e74b4c8a74e5687d5140002370936 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    156 schema:name Transcription, Genetic
    157 rdf:type schema:DefinedTerm
    158 Na7b151b6e2c64759af3d4a773c1095b0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    159 schema:name Female
    160 rdf:type schema:DefinedTerm
    161 Nb295ea8120264067b09d93ce9a4931f6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    162 schema:name Mice
    163 rdf:type schema:DefinedTerm
    164 Nb7153b4338684edea30341d394bd2355 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    165 schema:name Sequence Analysis, RNA
    166 rdf:type schema:DefinedTerm
    167 Nb9dbfdb2284d425f884340591f39d057 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    168 schema:name Genetic Association Studies
    169 rdf:type schema:DefinedTerm
    170 Nc87b9028c79c4755ab14a4753795639a schema:issueNumber 5
    171 rdf:type schema:PublicationIssue
    172 Ncc2e80dbb97c42ec9ead6a568a384958 rdf:first sg:person.01170225154.35
    173 rdf:rest N545a498765764fec87a6641179b8c8eb
    174 Nd2089cebaee848e4aa34667bb68c9f38 rdf:first sg:person.01243646203.36
    175 rdf:rest N4f42d74a7c454026a5db9b09db97d7e8
    176 Nd589ebed30a7404b8b6f0e393d08944b rdf:first sg:person.01222432021.01
    177 rdf:rest N76069f599ec14f0c8851d4984c23aa36
    178 Ndc6bf994cf2744cb90b0c12597583d2c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    179 schema:name Transcription Factors
    180 rdf:type schema:DefinedTerm
    181 Ne347b8331bd44701929b993e72727294 schema:volumeNumber 29
    182 rdf:type schema:PublicationVolume
    183 Ne4f7ad52b8d4444997e14a8290dec0ec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    184 schema:name Dendritic Cells
    185 rdf:type schema:DefinedTerm
    186 Ne5a1d6a728174613bc78d055fb5c5adf schema:name nlm_unique_id
    187 schema:value 9604648
    188 rdf:type schema:PropertyValue
    189 Nea99d0bb59f0478699875fa5c5384a59 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    190 schema:name RNA Polymerase II
    191 rdf:type schema:DefinedTerm
    192 Nf111730a602d4fb4a67ee9f7f6b74acb rdf:first sg:person.0645200471.91
    193 rdf:rest Ncc2e80dbb97c42ec9ead6a568a384958
    194 Nfa81b64e07234372aa080075f3077569 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    195 schema:name RNA
    196 rdf:type schema:DefinedTerm
    197 Nfd4043cb3e674f35a888515480550b0d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    198 schema:name Cells, Cultured
    199 rdf:type schema:DefinedTerm
    200 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    201 schema:name Biological Sciences
    202 rdf:type schema:DefinedTerm
    203 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    204 schema:name Genetics
    205 rdf:type schema:DefinedTerm
    206 sg:grant.2355082 http://pending.schema.org/fundedItem sg:pub.10.1038/nbt.1861
    207 rdf:type schema:MonetaryGrant
    208 sg:grant.2355252 http://pending.schema.org/fundedItem sg:pub.10.1038/nbt.1861
    209 rdf:type schema:MonetaryGrant
    210 sg:grant.2675020 http://pending.schema.org/fundedItem sg:pub.10.1038/nbt.1861
    211 rdf:type schema:MonetaryGrant
    212 sg:grant.2698981 http://pending.schema.org/fundedItem sg:pub.10.1038/nbt.1861
    213 rdf:type schema:MonetaryGrant
    214 sg:journal.1115214 schema:issn 1087-0156
    215 1546-1696
    216 schema:name Nature Biotechnology
    217 rdf:type schema:Periodical
    218 sg:person.01000014215.36 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    219 schema:familyName Adiconis
    220 schema:givenName Xian
    221 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000014215.36
    222 rdf:type schema:Person
    223 sg:person.01076324365.97 schema:affiliation https://www.grid.ac/institutes/grid.116068.8
    224 schema:familyName Rabani
    225 schema:givenName Michal
    226 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01076324365.97
    227 rdf:type schema:Person
    228 sg:person.01113613366.14 schema:affiliation https://www.grid.ac/institutes/grid.9619.7
    229 schema:familyName Friedman
    230 schema:givenName Nir
    231 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113613366.14
    232 rdf:type schema:Person
    233 sg:person.01170225154.35 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    234 schema:familyName Nusbaum
    235 schema:givenName Chad
    236 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01170225154.35
    237 rdf:type schema:Person
    238 sg:person.01213005106.80 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    239 schema:familyName Garber
    240 schema:givenName Manuel
    241 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213005106.80
    242 rdf:type schema:Person
    243 sg:person.01222432021.01 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    244 schema:familyName Levin
    245 schema:givenName Joshua Z
    246 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01222432021.01
    247 rdf:type schema:Person
    248 sg:person.01243646203.36 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    249 schema:familyName Raychowdhury
    250 schema:givenName Raktima
    251 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01243646203.36
    252 rdf:type schema:Person
    253 sg:person.01311753732.26 schema:affiliation https://www.grid.ac/institutes/grid.116068.8
    254 schema:familyName Regev
    255 schema:givenName Aviv
    256 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01311753732.26
    257 rdf:type schema:Person
    258 sg:person.01330120620.44 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    259 schema:familyName Amit
    260 schema:givenName Ido
    261 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01330120620.44
    262 rdf:type schema:Person
    263 sg:person.0631561714.29 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    264 schema:familyName Hacohen
    265 schema:givenName Nir
    266 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0631561714.29
    267 rdf:type schema:Person
    268 sg:person.0645200471.91 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    269 schema:familyName Gnirke
    270 schema:givenName Andreas
    271 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645200471.91
    272 rdf:type schema:Person
    273 sg:person.0650451313.47 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
    274 schema:familyName Fan
    275 schema:givenName Lin
    276 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650451313.47
    277 rdf:type schema:Person
    278 sg:pub.10.1038/nature06496 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043696128
    279 https://doi.org/10.1038/nature06496
    280 rdf:type schema:CreativeWork
    281 sg:pub.10.1038/nbt.1499 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046058321
    282 https://doi.org/10.1038/nbt.1499
    283 rdf:type schema:CreativeWork
    284 sg:pub.10.1038/nbt.1633 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025339324
    285 https://doi.org/10.1038/nbt.1633
    286 rdf:type schema:CreativeWork
    287 sg:pub.10.1038/nbt1061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005901943
    288 https://doi.org/10.1038/nbt1061
    289 rdf:type schema:CreativeWork
    290 sg:pub.10.1038/nbt1385 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053259870
    291 https://doi.org/10.1038/nbt1385
    292 rdf:type schema:CreativeWork
    293 sg:pub.10.1038/ng1987 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032102166
    294 https://doi.org/10.1038/ng1987
    295 rdf:type schema:CreativeWork
    296 sg:pub.10.1038/ni.1699 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025578738
    297 https://doi.org/10.1038/ni.1699
    298 rdf:type schema:CreativeWork
    299 sg:pub.10.1038/nmeth.1226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045381177
    300 https://doi.org/10.1038/nmeth.1226
    301 rdf:type schema:CreativeWork
    302 sg:pub.10.1038/nmeth.1491 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019899367
    303 https://doi.org/10.1038/nmeth.1491
    304 rdf:type schema:CreativeWork
    305 sg:pub.10.1186/1471-2164-11-259 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044029433
    306 https://doi.org/10.1186/1471-2164-11-259
    307 rdf:type schema:CreativeWork
    308 sg:pub.10.1186/1471-2164-6-75 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000774804
    309 https://doi.org/10.1186/1471-2164-6-75
    310 rdf:type schema:CreativeWork
    311 sg:pub.10.1186/gb-2002-3-7-research0034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039751959
    312 https://doi.org/10.1186/gb-2002-3-7-research0034
    313 rdf:type schema:CreativeWork
    314 sg:pub.10.1186/gb-2009-10-3-r25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049583368
    315 https://doi.org/10.1186/gb-2009-10-3-r25
    316 rdf:type schema:CreativeWork
    317 https://app.dimensions.ai/details/publication/pub.1074814991 schema:CreativeWork
    318 https://app.dimensions.ai/details/publication/pub.1077587903 schema:CreativeWork
    319 https://doi.org/10.1002/yea.1548 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014770530
    320 rdf:type schema:CreativeWork
    321 https://doi.org/10.1016/0092-8674(94)90221-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042602817
    322 rdf:type schema:CreativeWork
    323 https://doi.org/10.1016/j.molcel.2004.06.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035947017
    324 rdf:type schema:CreativeWork
    325 https://doi.org/10.1016/j.ygeno.2006.03.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038813539
    326 rdf:type schema:CreativeWork
    327 https://doi.org/10.1016/s0092-8674(01)00449-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008090278
    328 rdf:type schema:CreativeWork
    329 https://doi.org/10.1017/s1355838299981190 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054923946
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1038/msb.2008.59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006941967
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1038/msb.2009.84 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016953373
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.1038/msb.2010.38 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010018471
    336 rdf:type schema:CreativeWork
    337 https://doi.org/10.1038/msb4100115 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052922326
    338 rdf:type schema:CreativeWork
    339 https://doi.org/10.1039/b911233b schema:sameAs https://app.dimensions.ai/details/publication/pub.1028841108
    340 rdf:type schema:CreativeWork
    341 https://doi.org/10.1073/pnas.0506580102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037705714
    342 rdf:type schema:CreativeWork
    343 https://doi.org/10.1073/pnas.0610439104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040471829
    344 rdf:type schema:CreativeWork
    345 https://doi.org/10.1073/pnas.092538799 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009364821
    346 rdf:type schema:CreativeWork
    347 https://doi.org/10.1089/cmb.2008.13tt schema:sameAs https://app.dimensions.ai/details/publication/pub.1059245763
    348 rdf:type schema:CreativeWork
    349 https://doi.org/10.1093/bioinformatics/bth941 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050276898
    350 rdf:type schema:CreativeWork
    351 https://doi.org/10.1093/bioinformatics/btp120 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012425816
    352 rdf:type schema:CreativeWork
    353 https://doi.org/10.1093/nar/gkf682 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016001493
    354 rdf:type schema:CreativeWork
    355 https://doi.org/10.1093/nar/gkl164 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019792439
    356 rdf:type schema:CreativeWork
    357 https://doi.org/10.1093/nar/gkl842 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008035809
    358 rdf:type schema:CreativeWork
    359 https://doi.org/10.1093/nar/gkm929 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051689742
    360 rdf:type schema:CreativeWork
    361 https://doi.org/10.1093/nar/gkn766 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032292161
    362 rdf:type schema:CreativeWork
    363 https://doi.org/10.1093/nar/gkp542 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042357646
    364 rdf:type schema:CreativeWork
    365 https://doi.org/10.1093/nar/gkp939 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038538216
    366 rdf:type schema:CreativeWork
    367 https://doi.org/10.1126/science.1162228 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013963804
    368 rdf:type schema:CreativeWork
    369 https://doi.org/10.1126/science.1171347 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077935333
    370 rdf:type schema:CreativeWork
    371 https://doi.org/10.1126/science.1174062 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062460150
    372 rdf:type schema:CreativeWork
    373 https://doi.org/10.1126/science.1179050 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044210053
    374 rdf:type schema:CreativeWork
    375 https://doi.org/10.1126/science.281.5379.1001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062562056
    376 rdf:type schema:CreativeWork
    377 https://doi.org/10.1128/mcb.00945-06 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023813666
    378 rdf:type schema:CreativeWork
    379 https://doi.org/10.1128/mcb.17.2.809 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006049550
    380 rdf:type schema:CreativeWork
    381 https://doi.org/10.1137/s1052623496303470 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062883551
    382 rdf:type schema:CreativeWork
    383 https://doi.org/10.1214/aoms/1177732360 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064402573
    384 rdf:type schema:CreativeWork
    385 https://doi.org/10.1261/rna.1136108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047586134
    386 rdf:type schema:CreativeWork
    387 https://doi.org/10.1371/journal.pcbi.1000021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046266506
    388 rdf:type schema:CreativeWork
    389 https://www.grid.ac/institutes/grid.116068.8 schema:alternateName Massachusetts Institute of Technology
    390 schema:name Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
    391 Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
    392 Howard Hughes Medical Institute, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
    393 rdf:type schema:Organization
    394 https://www.grid.ac/institutes/grid.66859.34 schema:alternateName Broad Institute
    395 schema:name Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
    396 rdf:type schema:Organization
    397 https://www.grid.ac/institutes/grid.9619.7 schema:alternateName Hebrew University of Jerusalem
    398 schema:name Institute of Life Sciences, Hebrew University, Jerusalem, Israel.
    399 School of Computer Science, Hebrew University, Jerusalem, Israel.
    400 rdf:type schema:Organization
     




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


    ...