Processing, visualising and reconstructing network models from single-cell data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-03

AUTHORS

Steven Woodhouse, Victoria Moignard, Berthold Göttgens, Jasmin Fisher

ABSTRACT

New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review, we will discuss methods for visualisation and interpretation of single-cell gene expression data, and the computational analysis needed to go from raw data to predictive executable models of gene regulatory network function. We will focus primarily on single-cell real-time quantitative PCR and RNA-sequencing data, but much of what we cover will also be relevant to other platforms, such as the mass cytometry technology for high-dimensional single-cell proteomics. More... »

PAGES

256

References to SciGraph publications

  • 2012-01. Counting absolute numbers of molecules using unique molecular identifiers in NATURE METHODS
  • 2014-06. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation in NATURE
  • 2015-05. Spatial reconstruction of single-cell gene expression data in NATURE BIOTECHNOLOGY
  • 2014-12-03. Deconstructing transcriptional heterogeneity in pluripotent stem cells in NATURE
  • 2012-11. Nanog-dependent feedback loops regulate murine embryonic stem cell heterogeneity in NATURE CELL BIOLOGY
  • 2008. Diffusion Maps - a Probabilistic Interpretation for Spectral Embedding and Clustering Algorithms in PRINCIPAL MANIFOLDS FOR DATA VISUALIZATION AND DIMENSION REDUCTION
  • 2015. Synthesising Executable Gene Regulatory Networks from Single-Cell Gene Expression Data in COMPUTER AIDED VERIFICATION
  • 2003. Relevance Networks: A First Step Toward Finding Genetic Regulatory Networks Within Microarray Data in THE ANALYSIS OF GENE EXPRESSION DATA
  • 2011-12. Single-cell dissection of transcriptional heterogeneity in human colon tumors in NATURE BIOTECHNOLOGY
  • 2014-04. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells in NATURE BIOTECHNOLOGY
  • 2011-10. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE in NATURE BIOTECHNOLOGY
  • 2015-03. Decoding the regulatory network of early blood development from single-cell gene expression measurements in NATURE BIOTECHNOLOGY
  • 2012-03. Inferring rules of lineage commitment in haematopoiesis in NATURE CELL BIOLOGY
  • 2009-05. mRNA-Seq whole-transcriptome analysis of a single cell in NATURE METHODS
  • 2015-09. Single-cell messenger RNA sequencing reveals rare intestinal cell types in NATURE
  • 2015-12. A geometric viewpoint of manifold learning in APPLIED INFORMATICS
  • 2015-03. Computational and analytical challenges in single-cell transcriptomics in NATURE REVIEWS GENETICS
  • 2013-12. Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level in NATURE COMMUNICATIONS
  • 2014-02. Quantitative single-cell RNA-seq with unique molecular identifiers in NATURE METHODS
  • 2013-06. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia in NATURE BIOTECHNOLOGY
  • 2013-11. Smart-seq2 for sensitive full-length transcriptome profiling in single cells in NATURE METHODS
  • 2013-04. Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis in NATURE CELL BIOLOGY
  • 2012-08. Wisdom of crowds for robust gene network inference in NATURE METHODS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/icb.2015.102

    DOI

    http://dx.doi.org/10.1038/icb.2015.102

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1042998360

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26577213


    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": "Bayes Theorem", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cluster Analysis", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Computational Biology", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Profiling", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Regulatory Networks", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genomics", 
            "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": "Principal Component Analysis", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Single-Cell Analysis", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Wellcome / MRC Cambridge Stem Cell Institute", 
              "id": "https://www.grid.ac/institutes/grid.449973.4", 
              "name": [
                "Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK", 
                "Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Woodhouse", 
            "givenName": "Steven", 
            "id": "sg:person.01166423115.58", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01166423115.58"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Wellcome / MRC Cambridge Stem Cell Institute", 
              "id": "https://www.grid.ac/institutes/grid.449973.4", 
              "name": [
                "Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK", 
                "Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Moignard", 
            "givenName": "Victoria", 
            "id": "sg:person.01270122656.75", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01270122656.75"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Wellcome / MRC Cambridge Stem Cell Institute", 
              "id": "https://www.grid.ac/institutes/grid.449973.4", 
              "name": [
                "Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK", 
                "Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK"
              ], 
              "type": "Organization"
            }, 
            "familyName": "G\u00f6ttgens", 
            "givenName": "Berthold", 
            "id": "sg:person.07575367437.14", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07575367437.14"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Cambridge", 
              "id": "https://www.grid.ac/institutes/grid.5335.0", 
              "name": [
                "Microsoft Research, Cambridge, UK", 
                "Department of Biochemistry, University of Cambridge, Cambridge, UK"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fisher", 
            "givenName": "Jasmin", 
            "id": "sg:person.01302263266.70", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01302263266.70"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.stem.2015.04.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000008206"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1105809", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002199042"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2007.02.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003440590"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg3833", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004107723", 
              "https://doi.org/10.1038/nrg3833"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncb2709", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005039204", 
              "https://doi.org/10.1038/ncb2709"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1259425", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005046019"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.2639", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006291172", 
              "https://doi.org/10.1038/nmeth.2639"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.stem.2013.07.017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006509010"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.1991", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007715803", 
              "https://doi.org/10.1038/nbt.1991"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.3154", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007848623", 
              "https://doi.org/10.1038/nbt.3154"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.3192", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009318815", 
              "https://doi.org/10.1038/nbt.3192"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp120", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012425816"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature13920", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012885463", 
              "https://doi.org/10.1038/nature13920"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1250212", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013396046"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/0-387-21679-0_19", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015538711", 
              "https://doi.org/10.1007/0-387-21679-0_19"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0012776", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016959201"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1778", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017388763", 
              "https://doi.org/10.1038/nmeth.1778"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.celrep.2015.05.016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018482496"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2859", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018546171", 
              "https://doi.org/10.1038/nbt.2859"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.devcel.2010.02.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018728907"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2015.05.047", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018918462"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1162/089976698300017467", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019671707"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.celrep.2012.08.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019883673"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2014.04.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022072709"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1315", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022155307", 
              "https://doi.org/10.1038/nmeth.1315"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1315", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022155307", 
              "https://doi.org/10.1038/nmeth.1315"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-73750-6_10", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022235345", 
              "https://doi.org/10.1007/978-3-540-73750-6_10"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-73750-6_10", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022235345", 
              "https://doi.org/10.1007/978-3-540-73750-6_10"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.2016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023029250", 
              "https://doi.org/10.1038/nmeth.2016"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40535-015-0006-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023675030", 
              "https://doi.org/10.1186/s40535-015-0006-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40535-015-0006-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023675030", 
              "https://doi.org/10.1186/s40535-015-0006-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.110882.110", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024095958"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0500334102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024530701"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bies.201300102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025050976"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btq057", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025260149"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncb2442", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027758587", 
              "https://doi.org/10.1038/ncb2442"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.2772", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029706604", 
              "https://doi.org/10.1038/nmeth.2772"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2038", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029818016", 
              "https://doi.org/10.1038/nbt.2038"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2038", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029818016", 
              "https://doi.org/10.1038/nbt.2038"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2594", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031239463", 
              "https://doi.org/10.1038/nbt.2594"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2594", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031239463", 
              "https://doi.org/10.1038/nbt.2594"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-21690-4_38", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036257811", 
              "https://doi.org/10.1007/978-3-319-21690-4_38"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3389/fbioe.2014.00075", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036734220"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1247651", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037007803"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.1004126", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037733887"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btv325", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041568519"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature14966", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044817288", 
              "https://doi.org/10.1038/nature14966"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.121095.111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044818605"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.celrep.2014.04.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045886011"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1254257", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046815039"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btv257", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047521214"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature13437", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048753935", 
              "https://doi.org/10.1038/nature13437"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/332306.332355", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049104539"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/332306.332355", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049104539"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymeth.2012.10.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049811567"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymeth.2012.10.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049811567"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncb2603", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050160022", 
              "https://doi.org/10.1038/ncb2603"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2012.08.023", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050505969"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkq1182", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051349931"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.aaa1934", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051709523"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1745-3984.2003.tb01108.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052250038"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncomms3924", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052424364", 
              "https://doi.org/10.1038/ncomms3924"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1250689", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052565143"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btu638", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053282140"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/bts635", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053365587"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2016-03", 
        "datePublishedReg": "2016-03-01", 
        "description": "New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review, we will discuss methods for visualisation and interpretation of single-cell gene expression data, and the computational analysis needed to go from raw data to predictive executable models of gene regulatory network function. We will focus primarily on single-cell real-time quantitative PCR and RNA-sequencing data, but much of what we cover will also be relevant to other platforms, such as the mass cytometry technology for high-dimensional single-cell proteomics. ", 
        "genre": "research_article", 
        "id": "sg:pub.10.1038/icb.2015.102", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.5142341", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2751786", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3498582", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.4106962", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1019561", 
            "issn": [
              "0818-9641", 
              "1440-1711"
            ], 
            "name": "Immunology and Cell Biology", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "94"
          }
        ], 
        "name": "Processing, visualising and reconstructing network models from single-cell data", 
        "pagination": "256", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "ccd125be116ae896e23ac16128902d0c3e2159b67c60160a96aeaf69916a14d9"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "26577213"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "8706300"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/icb.2015.102"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1042998360"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/icb.2015.102", 
          "https://app.dimensions.ai/details/publication/pub.1042998360"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T00:08", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8695_00000475.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://www.nature.com/articles/icb2015102"
      }
    ]
     

    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/icb.2015.102'

    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/icb.2015.102'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/icb.2015.102'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/icb.2015.102'


     

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

    344 TRIPLES      21 PREDICATES      98 URIs      32 LITERALS      20 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/icb.2015.102 schema:about N002601bc7f684261b7bd551a36776189
    2 N09d1f16cdff4426a92fd08ed1b6bdb3d
    3 N0d385e0efb8b42ecbf32597324059fa6
    4 N1364c603f724471da69255f383e8b09b
    5 N58ffd45645f541aba276724ff668b6f6
    6 N7c31792084ac4116b44ad3a9b3edcfd8
    7 Naf6c34e26b2a4f95a9bbf552d10e8e93
    8 Ncfa87676e41a412586899a95695bd4f2
    9 Ne289716388d24ac0b6ab5a173c3c724e
    10 Neb5d879f7dfc4e2a82c3dd6d4541c06f
    11 Nf44c0b39772d4c8cb7deb69a04390969
    12 anzsrc-for:06
    13 anzsrc-for:0604
    14 schema:author N47432be2ddec4020a8e30af2d9ca1f16
    15 schema:citation sg:pub.10.1007/0-387-21679-0_19
    16 sg:pub.10.1007/978-3-319-21690-4_38
    17 sg:pub.10.1007/978-3-540-73750-6_10
    18 sg:pub.10.1038/nature13437
    19 sg:pub.10.1038/nature13920
    20 sg:pub.10.1038/nature14966
    21 sg:pub.10.1038/nbt.1991
    22 sg:pub.10.1038/nbt.2038
    23 sg:pub.10.1038/nbt.2594
    24 sg:pub.10.1038/nbt.2859
    25 sg:pub.10.1038/nbt.3154
    26 sg:pub.10.1038/nbt.3192
    27 sg:pub.10.1038/ncb2442
    28 sg:pub.10.1038/ncb2603
    29 sg:pub.10.1038/ncb2709
    30 sg:pub.10.1038/ncomms3924
    31 sg:pub.10.1038/nmeth.1315
    32 sg:pub.10.1038/nmeth.1778
    33 sg:pub.10.1038/nmeth.2016
    34 sg:pub.10.1038/nmeth.2639
    35 sg:pub.10.1038/nmeth.2772
    36 sg:pub.10.1038/nrg3833
    37 sg:pub.10.1186/s40535-015-0006-6
    38 https://doi.org/10.1002/bies.201300102
    39 https://doi.org/10.1016/j.cell.2007.02.006
    40 https://doi.org/10.1016/j.cell.2012.08.023
    41 https://doi.org/10.1016/j.cell.2014.04.005
    42 https://doi.org/10.1016/j.cell.2015.05.047
    43 https://doi.org/10.1016/j.celrep.2012.08.003
    44 https://doi.org/10.1016/j.celrep.2014.04.011
    45 https://doi.org/10.1016/j.celrep.2015.05.016
    46 https://doi.org/10.1016/j.devcel.2010.02.012
    47 https://doi.org/10.1016/j.stem.2013.07.017
    48 https://doi.org/10.1016/j.stem.2015.04.004
    49 https://doi.org/10.1016/j.ymeth.2012.10.004
    50 https://doi.org/10.1073/pnas.0500334102
    51 https://doi.org/10.1093/bioinformatics/btp120
    52 https://doi.org/10.1093/bioinformatics/btq057
    53 https://doi.org/10.1093/bioinformatics/bts635
    54 https://doi.org/10.1093/bioinformatics/btu638
    55 https://doi.org/10.1093/bioinformatics/btv257
    56 https://doi.org/10.1093/bioinformatics/btv325
    57 https://doi.org/10.1093/nar/gkq1182
    58 https://doi.org/10.1101/gr.110882.110
    59 https://doi.org/10.1101/gr.121095.111
    60 https://doi.org/10.1111/j.1745-3984.2003.tb01108.x
    61 https://doi.org/10.1126/science.1105809
    62 https://doi.org/10.1126/science.1247651
    63 https://doi.org/10.1126/science.1250212
    64 https://doi.org/10.1126/science.1250689
    65 https://doi.org/10.1126/science.1254257
    66 https://doi.org/10.1126/science.1259425
    67 https://doi.org/10.1126/science.aaa1934
    68 https://doi.org/10.1145/332306.332355
    69 https://doi.org/10.1162/089976698300017467
    70 https://doi.org/10.1371/journal.pgen.1004126
    71 https://doi.org/10.1371/journal.pone.0012776
    72 https://doi.org/10.3389/fbioe.2014.00075
    73 schema:datePublished 2016-03
    74 schema:datePublishedReg 2016-03-01
    75 schema:description New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review, we will discuss methods for visualisation and interpretation of single-cell gene expression data, and the computational analysis needed to go from raw data to predictive executable models of gene regulatory network function. We will focus primarily on single-cell real-time quantitative PCR and RNA-sequencing data, but much of what we cover will also be relevant to other platforms, such as the mass cytometry technology for high-dimensional single-cell proteomics.
    76 schema:genre research_article
    77 schema:inLanguage en
    78 schema:isAccessibleForFree true
    79 schema:isPartOf N987257e7a558427983a56ae573ba96ea
    80 Nc03cdd5895f84640bbd31fea9039321d
    81 sg:journal.1019561
    82 schema:name Processing, visualising and reconstructing network models from single-cell data
    83 schema:pagination 256
    84 schema:productId N1cea166fd6dc4aaaa2d01ea134c61764
    85 N2cc17744f9f743ab8af08b0a48aabc07
    86 N3c8faf9493da452a9d3e6b237fa967c8
    87 Nc3877c8df879448f89488303022f5b28
    88 Ne6371295e1b34df4a387c62f22657375
    89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042998360
    90 https://doi.org/10.1038/icb.2015.102
    91 schema:sdDatePublished 2019-04-11T00:08
    92 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    93 schema:sdPublisher N792fa784d8dc4d5f9b1d372dbebb8516
    94 schema:url https://www.nature.com/articles/icb2015102
    95 sgo:license sg:explorer/license/
    96 sgo:sdDataset articles
    97 rdf:type schema:ScholarlyArticle
    98 N002601bc7f684261b7bd551a36776189 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    99 schema:name Bayes Theorem
    100 rdf:type schema:DefinedTerm
    101 N09d1f16cdff4426a92fd08ed1b6bdb3d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    102 schema:name Animals
    103 rdf:type schema:DefinedTerm
    104 N0d385e0efb8b42ecbf32597324059fa6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    105 schema:name Computational Biology
    106 rdf:type schema:DefinedTerm
    107 N1364c603f724471da69255f383e8b09b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    108 schema:name Principal Component Analysis
    109 rdf:type schema:DefinedTerm
    110 N1cea166fd6dc4aaaa2d01ea134c61764 schema:name nlm_unique_id
    111 schema:value 8706300
    112 rdf:type schema:PropertyValue
    113 N2cc17744f9f743ab8af08b0a48aabc07 schema:name pubmed_id
    114 schema:value 26577213
    115 rdf:type schema:PropertyValue
    116 N3c8faf9493da452a9d3e6b237fa967c8 schema:name doi
    117 schema:value 10.1038/icb.2015.102
    118 rdf:type schema:PropertyValue
    119 N47432be2ddec4020a8e30af2d9ca1f16 rdf:first sg:person.01166423115.58
    120 rdf:rest N80dda2e330b3421593d216ef96ce091d
    121 N58ffd45645f541aba276724ff668b6f6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    122 schema:name Gene Expression Profiling
    123 rdf:type schema:DefinedTerm
    124 N792fa784d8dc4d5f9b1d372dbebb8516 schema:name Springer Nature - SN SciGraph project
    125 rdf:type schema:Organization
    126 N7c31792084ac4116b44ad3a9b3edcfd8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    127 schema:name Gene Regulatory Networks
    128 rdf:type schema:DefinedTerm
    129 N80dda2e330b3421593d216ef96ce091d rdf:first sg:person.01270122656.75
    130 rdf:rest N82455e5296094a7b97bf2cfdcea50000
    131 N82455e5296094a7b97bf2cfdcea50000 rdf:first sg:person.07575367437.14
    132 rdf:rest Naaffd1608f03402ebcd05a2b6012f3d4
    133 N987257e7a558427983a56ae573ba96ea schema:volumeNumber 94
    134 rdf:type schema:PublicationVolume
    135 Naaffd1608f03402ebcd05a2b6012f3d4 rdf:first sg:person.01302263266.70
    136 rdf:rest rdf:nil
    137 Naf6c34e26b2a4f95a9bbf552d10e8e93 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    138 schema:name Single-Cell Analysis
    139 rdf:type schema:DefinedTerm
    140 Nc03cdd5895f84640bbd31fea9039321d schema:issueNumber 3
    141 rdf:type schema:PublicationIssue
    142 Nc3877c8df879448f89488303022f5b28 schema:name dimensions_id
    143 schema:value pub.1042998360
    144 rdf:type schema:PropertyValue
    145 Ncfa87676e41a412586899a95695bd4f2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    146 schema:name High-Throughput Nucleotide Sequencing
    147 rdf:type schema:DefinedTerm
    148 Ne289716388d24ac0b6ab5a173c3c724e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    149 schema:name Cluster Analysis
    150 rdf:type schema:DefinedTerm
    151 Ne6371295e1b34df4a387c62f22657375 schema:name readcube_id
    152 schema:value ccd125be116ae896e23ac16128902d0c3e2159b67c60160a96aeaf69916a14d9
    153 rdf:type schema:PropertyValue
    154 Neb5d879f7dfc4e2a82c3dd6d4541c06f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    155 schema:name Genomics
    156 rdf:type schema:DefinedTerm
    157 Nf44c0b39772d4c8cb7deb69a04390969 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    158 schema:name Humans
    159 rdf:type schema:DefinedTerm
    160 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    161 schema:name Biological Sciences
    162 rdf:type schema:DefinedTerm
    163 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    164 schema:name Genetics
    165 rdf:type schema:DefinedTerm
    166 sg:grant.2751786 http://pending.schema.org/fundedItem sg:pub.10.1038/icb.2015.102
    167 rdf:type schema:MonetaryGrant
    168 sg:grant.3498582 http://pending.schema.org/fundedItem sg:pub.10.1038/icb.2015.102
    169 rdf:type schema:MonetaryGrant
    170 sg:grant.4106962 http://pending.schema.org/fundedItem sg:pub.10.1038/icb.2015.102
    171 rdf:type schema:MonetaryGrant
    172 sg:grant.5142341 http://pending.schema.org/fundedItem sg:pub.10.1038/icb.2015.102
    173 rdf:type schema:MonetaryGrant
    174 sg:journal.1019561 schema:issn 0818-9641
    175 1440-1711
    176 schema:name Immunology and Cell Biology
    177 rdf:type schema:Periodical
    178 sg:person.01166423115.58 schema:affiliation https://www.grid.ac/institutes/grid.449973.4
    179 schema:familyName Woodhouse
    180 schema:givenName Steven
    181 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01166423115.58
    182 rdf:type schema:Person
    183 sg:person.01270122656.75 schema:affiliation https://www.grid.ac/institutes/grid.449973.4
    184 schema:familyName Moignard
    185 schema:givenName Victoria
    186 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01270122656.75
    187 rdf:type schema:Person
    188 sg:person.01302263266.70 schema:affiliation https://www.grid.ac/institutes/grid.5335.0
    189 schema:familyName Fisher
    190 schema:givenName Jasmin
    191 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01302263266.70
    192 rdf:type schema:Person
    193 sg:person.07575367437.14 schema:affiliation https://www.grid.ac/institutes/grid.449973.4
    194 schema:familyName Göttgens
    195 schema:givenName Berthold
    196 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07575367437.14
    197 rdf:type schema:Person
    198 sg:pub.10.1007/0-387-21679-0_19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015538711
    199 https://doi.org/10.1007/0-387-21679-0_19
    200 rdf:type schema:CreativeWork
    201 sg:pub.10.1007/978-3-319-21690-4_38 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036257811
    202 https://doi.org/10.1007/978-3-319-21690-4_38
    203 rdf:type schema:CreativeWork
    204 sg:pub.10.1007/978-3-540-73750-6_10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022235345
    205 https://doi.org/10.1007/978-3-540-73750-6_10
    206 rdf:type schema:CreativeWork
    207 sg:pub.10.1038/nature13437 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048753935
    208 https://doi.org/10.1038/nature13437
    209 rdf:type schema:CreativeWork
    210 sg:pub.10.1038/nature13920 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012885463
    211 https://doi.org/10.1038/nature13920
    212 rdf:type schema:CreativeWork
    213 sg:pub.10.1038/nature14966 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044817288
    214 https://doi.org/10.1038/nature14966
    215 rdf:type schema:CreativeWork
    216 sg:pub.10.1038/nbt.1991 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007715803
    217 https://doi.org/10.1038/nbt.1991
    218 rdf:type schema:CreativeWork
    219 sg:pub.10.1038/nbt.2038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029818016
    220 https://doi.org/10.1038/nbt.2038
    221 rdf:type schema:CreativeWork
    222 sg:pub.10.1038/nbt.2594 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031239463
    223 https://doi.org/10.1038/nbt.2594
    224 rdf:type schema:CreativeWork
    225 sg:pub.10.1038/nbt.2859 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018546171
    226 https://doi.org/10.1038/nbt.2859
    227 rdf:type schema:CreativeWork
    228 sg:pub.10.1038/nbt.3154 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007848623
    229 https://doi.org/10.1038/nbt.3154
    230 rdf:type schema:CreativeWork
    231 sg:pub.10.1038/nbt.3192 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009318815
    232 https://doi.org/10.1038/nbt.3192
    233 rdf:type schema:CreativeWork
    234 sg:pub.10.1038/ncb2442 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027758587
    235 https://doi.org/10.1038/ncb2442
    236 rdf:type schema:CreativeWork
    237 sg:pub.10.1038/ncb2603 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050160022
    238 https://doi.org/10.1038/ncb2603
    239 rdf:type schema:CreativeWork
    240 sg:pub.10.1038/ncb2709 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005039204
    241 https://doi.org/10.1038/ncb2709
    242 rdf:type schema:CreativeWork
    243 sg:pub.10.1038/ncomms3924 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052424364
    244 https://doi.org/10.1038/ncomms3924
    245 rdf:type schema:CreativeWork
    246 sg:pub.10.1038/nmeth.1315 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022155307
    247 https://doi.org/10.1038/nmeth.1315
    248 rdf:type schema:CreativeWork
    249 sg:pub.10.1038/nmeth.1778 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017388763
    250 https://doi.org/10.1038/nmeth.1778
    251 rdf:type schema:CreativeWork
    252 sg:pub.10.1038/nmeth.2016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023029250
    253 https://doi.org/10.1038/nmeth.2016
    254 rdf:type schema:CreativeWork
    255 sg:pub.10.1038/nmeth.2639 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006291172
    256 https://doi.org/10.1038/nmeth.2639
    257 rdf:type schema:CreativeWork
    258 sg:pub.10.1038/nmeth.2772 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029706604
    259 https://doi.org/10.1038/nmeth.2772
    260 rdf:type schema:CreativeWork
    261 sg:pub.10.1038/nrg3833 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004107723
    262 https://doi.org/10.1038/nrg3833
    263 rdf:type schema:CreativeWork
    264 sg:pub.10.1186/s40535-015-0006-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023675030
    265 https://doi.org/10.1186/s40535-015-0006-6
    266 rdf:type schema:CreativeWork
    267 https://doi.org/10.1002/bies.201300102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025050976
    268 rdf:type schema:CreativeWork
    269 https://doi.org/10.1016/j.cell.2007.02.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003440590
    270 rdf:type schema:CreativeWork
    271 https://doi.org/10.1016/j.cell.2012.08.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050505969
    272 rdf:type schema:CreativeWork
    273 https://doi.org/10.1016/j.cell.2014.04.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022072709
    274 rdf:type schema:CreativeWork
    275 https://doi.org/10.1016/j.cell.2015.05.047 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018918462
    276 rdf:type schema:CreativeWork
    277 https://doi.org/10.1016/j.celrep.2012.08.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019883673
    278 rdf:type schema:CreativeWork
    279 https://doi.org/10.1016/j.celrep.2014.04.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045886011
    280 rdf:type schema:CreativeWork
    281 https://doi.org/10.1016/j.celrep.2015.05.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018482496
    282 rdf:type schema:CreativeWork
    283 https://doi.org/10.1016/j.devcel.2010.02.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018728907
    284 rdf:type schema:CreativeWork
    285 https://doi.org/10.1016/j.stem.2013.07.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006509010
    286 rdf:type schema:CreativeWork
    287 https://doi.org/10.1016/j.stem.2015.04.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000008206
    288 rdf:type schema:CreativeWork
    289 https://doi.org/10.1016/j.ymeth.2012.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049811567
    290 rdf:type schema:CreativeWork
    291 https://doi.org/10.1073/pnas.0500334102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024530701
    292 rdf:type schema:CreativeWork
    293 https://doi.org/10.1093/bioinformatics/btp120 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012425816
    294 rdf:type schema:CreativeWork
    295 https://doi.org/10.1093/bioinformatics/btq057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025260149
    296 rdf:type schema:CreativeWork
    297 https://doi.org/10.1093/bioinformatics/bts635 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053365587
    298 rdf:type schema:CreativeWork
    299 https://doi.org/10.1093/bioinformatics/btu638 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053282140
    300 rdf:type schema:CreativeWork
    301 https://doi.org/10.1093/bioinformatics/btv257 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047521214
    302 rdf:type schema:CreativeWork
    303 https://doi.org/10.1093/bioinformatics/btv325 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041568519
    304 rdf:type schema:CreativeWork
    305 https://doi.org/10.1093/nar/gkq1182 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051349931
    306 rdf:type schema:CreativeWork
    307 https://doi.org/10.1101/gr.110882.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024095958
    308 rdf:type schema:CreativeWork
    309 https://doi.org/10.1101/gr.121095.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044818605
    310 rdf:type schema:CreativeWork
    311 https://doi.org/10.1111/j.1745-3984.2003.tb01108.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1052250038
    312 rdf:type schema:CreativeWork
    313 https://doi.org/10.1126/science.1105809 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002199042
    314 rdf:type schema:CreativeWork
    315 https://doi.org/10.1126/science.1247651 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037007803
    316 rdf:type schema:CreativeWork
    317 https://doi.org/10.1126/science.1250212 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013396046
    318 rdf:type schema:CreativeWork
    319 https://doi.org/10.1126/science.1250689 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052565143
    320 rdf:type schema:CreativeWork
    321 https://doi.org/10.1126/science.1254257 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046815039
    322 rdf:type schema:CreativeWork
    323 https://doi.org/10.1126/science.1259425 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005046019
    324 rdf:type schema:CreativeWork
    325 https://doi.org/10.1126/science.aaa1934 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051709523
    326 rdf:type schema:CreativeWork
    327 https://doi.org/10.1145/332306.332355 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049104539
    328 rdf:type schema:CreativeWork
    329 https://doi.org/10.1162/089976698300017467 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019671707
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1371/journal.pgen.1004126 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037733887
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1371/journal.pone.0012776 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016959201
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.3389/fbioe.2014.00075 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036734220
    336 rdf:type schema:CreativeWork
    337 https://www.grid.ac/institutes/grid.449973.4 schema:alternateName Wellcome / MRC Cambridge Stem Cell Institute
    338 schema:name Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
    339 Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
    340 rdf:type schema:Organization
    341 https://www.grid.ac/institutes/grid.5335.0 schema:alternateName University of Cambridge
    342 schema:name Department of Biochemistry, University of Cambridge, Cambridge, UK
    343 Microsoft Research, Cambridge, UK
    344 rdf:type schema:Organization
     




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


    ...