Computational identification of putative lincRNAs in mouse embryonic stem cell View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Hui Liu, Jie Lyu, Hongbo Liu, Yang Gao, Jing Guo, Hongjuan He, Zhengbin Han, Yan Zhang, Qiong Wu

ABSTRACT

As the regulatory factors, lncRNAs play critical roles in embryonic stem cells. And lincRNAs are most widely studied lncRNAs, however, there might still might exist a large member of uncovered lncRNAs. In this study, we constructed the de novo assembly of transcriptome to detect 6,701 putative long intergenic non-coding transcripts (lincRNAs) expressed in mouse embryonic stem cells (ESCs), which might be incomplete with the lack coverage of 5' ends assessed by CAGE peaks. Comparing the TSS proximal regions between the known lincRNAs and their closet protein coding transcripts, our results revealed that the lincRNA TSS proximal regions are associated with the characteristic genomic and epigenetic features. Subsequently, 1,293 lincRNAs were corrected at their 5' ends using the putative lincRNA TSS regions predicted by the TSS proximal region prediction model based on genomic and epigenetic features. Finally, 43 putative lincRNAs were annotated by Gene Ontology terms. In conclusion, this work provides a novel catalog of mouse ESCs-expressed lincRNAs with the relatively complete transcript length, which might be useful for the investigation of transcriptional and post-transcriptional regulation of lincRNA in mouse ESCs and even mammalian development. More... »

PAGES

34892

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep34892

DOI

http://dx.doi.org/10.1038/srep34892

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009099485

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27713513


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": "Chromatin", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Epigenesis, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression Regulation, Developmental", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Machine Learning", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mice", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mouse Embryonic Stem Cells", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "RNA, Long Noncoding", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Transcription Initiation Site", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Harbin Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.19373.3f", 
          "name": [
            "School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Hui", 
        "id": "sg:person.01021140626.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021140626.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Baylor College of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.39382.33", 
          "name": [
            "Dan L. Duncan Cancer Center, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, 77030, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lyu", 
        "givenName": "Jie", 
        "id": "sg:person.010552444221.76", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010552444221.76"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harbin Medical University", 
          "id": "https://www.grid.ac/institutes/grid.410736.7", 
          "name": [
            "College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Hongbo", 
        "id": "sg:person.0753025426.94", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0753025426.94"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harbin Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.19373.3f", 
          "name": [
            "School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gao", 
        "givenName": "Yang", 
        "id": "sg:person.01235756516.88", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01235756516.88"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harbin Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.19373.3f", 
          "name": [
            "School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guo", 
        "givenName": "Jing", 
        "id": "sg:person.01140440275.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140440275.43"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harbin Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.19373.3f", 
          "name": [
            "School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "He", 
        "givenName": "Hongjuan", 
        "id": "sg:person.0634554317.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0634554317.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harbin Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.19373.3f", 
          "name": [
            "School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Han", 
        "givenName": "Zhengbin", 
        "id": "sg:person.01334631563.02", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334631563.02"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harbin Medical University", 
          "id": "https://www.grid.ac/institutes/grid.410736.7", 
          "name": [
            "College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Yan", 
        "id": "sg:person.01251615626.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01251615626.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harbin Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.19373.3f", 
          "name": [
            "School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wu", 
        "givenName": "Qiong", 
        "id": "sg:person.01131113612.76", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01131113612.76"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1093/nar/gku325", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002238968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature11233", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003047559", 
          "https://doi.org/10.1038/nature11233"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkt006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004840937"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.3317", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005140994", 
          "https://doi.org/10.1038/nmeth.3317"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2011/875309", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006345668"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1923", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006541515", 
          "https://doi.org/10.1038/nmeth.1923"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkp335", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007915246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkp335", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007915246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.devcel.2012.12.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008652964"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-13-s6-s4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008968188", 
          "https://doi.org/10.1186/1471-2105-13-s6-s4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00438-014-0882-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010544024", 
          "https://doi.org/10.1007/s00438-014-0882-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg3642", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010746394", 
          "https://doi.org/10.1038/nrg3642"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00335-015-9583-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011692857", 
          "https://doi.org/10.1007/s00335-015-9583-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00335-015-9583-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011692857", 
          "https://doi.org/10.1007/s00335-015-9583-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2008.01.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012430287"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.156232.113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013427894"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.132159.111", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013862605"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2014/416323", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014812994"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.7554/elife.02046", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015743913"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molcel.2011.08.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017411851"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature10398", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018204822", 
          "https://doi.org/10.1038/nature10398"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.stem.2015.03.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018793531"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.139618.112", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020375059"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.stem.2013.03.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021983761"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ncb437", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023498683", 
          "https://doi.org/10.1038/ncb437"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2164-13-455", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024040876", 
          "https://doi.org/10.1186/1471-2164-13-455"
        ], 
        "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.10.1007/s00441-014-1885-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027912826", 
          "https://doi.org/10.1007/s00441-014-1885-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00441-014-1885-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027912826", 
          "https://doi.org/10.1007/s00441-014-1885-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2007.02.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027946228"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.3192", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028060819", 
          "https://doi.org/10.1038/ng.3192"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/dev.105858", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028460790"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature11247", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029065430", 
          "https://doi.org/10.1038/nature11247"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13182", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029370855", 
          "https://doi.org/10.1038/nature13182"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/dmm.000232", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029924862"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00438-014-0952-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029950376", 
          "https://doi.org/10.1007/s00438-014-0952-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2012.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030124536", 
          "https://doi.org/10.1038/nprot.2012.016"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2484", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030687647", 
          "https://doi.org/10.1038/nrg2484"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.181974.114", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033420430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep23700", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034825005", 
          "https://doi.org/10.1038/srep23700"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0071152", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035017475"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkt997", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036657357"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13992", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036662703", 
          "https://doi.org/10.1038/nature13992"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13992", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036662703", 
          "https://doi.org/10.1038/nature13992"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/bti736", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036795811"
        ], 
        "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/gkv1157", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037937986"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkt818", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039201808"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.074906.107", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042580562"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.703", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043122239", 
          "https://doi.org/10.1038/ng.703"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.703", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043122239", 
          "https://doi.org/10.1038/ng.703"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2013.02.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043978712"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.3122", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045760294", 
          "https://doi.org/10.1038/nbt.3122"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0109443", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045775109"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1470", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047181882", 
          "https://doi.org/10.1038/nmeth.1470"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1470", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047181882", 
          "https://doi.org/10.1038/nmeth.1470"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/dev.116996", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047207739"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.078378.108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048137976"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.2596", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048926875", 
          "https://doi.org/10.1038/nbt.2596"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.stem.2014.05.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049735919"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bfgp/elv024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059412963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bib/bbv033", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059413086"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tmi.2014.2317520", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061696289"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tnnls.2014.2342533", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061718648"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2174/13892029113149990005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069178678"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-12", 
    "datePublishedReg": "2016-12-01", 
    "description": "As the regulatory factors, lncRNAs play critical roles in embryonic stem cells. And lincRNAs are most widely studied lncRNAs, however, there might still might exist a large member of uncovered lncRNAs. In this study, we constructed the de novo assembly of transcriptome to detect 6,701 putative long intergenic non-coding transcripts (lincRNAs) expressed in mouse embryonic stem cells (ESCs), which might be incomplete with the lack coverage of 5' ends assessed by CAGE peaks. Comparing the TSS proximal regions between the known lincRNAs and their closet protein coding transcripts, our results revealed that the lincRNA TSS proximal regions are associated with the characteristic genomic and epigenetic features. Subsequently, 1,293 lincRNAs were corrected at their 5' ends using the putative lincRNA TSS regions predicted by the TSS proximal region prediction model based on genomic and epigenetic features. Finally, 43 putative lincRNAs were annotated by Gene Ontology terms. In conclusion, this work provides a novel catalog of mouse ESCs-expressed lincRNAs with the relatively complete transcript length, which might be useful for the investigation of transcriptional and post-transcriptional regulation of lincRNA in mouse ESCs and even mammalian development.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/srep34892", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "6"
      }
    ], 
    "name": "Computational identification of putative lincRNAs in mouse embryonic stem cell", 
    "pagination": "34892", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "2b59fcae5ab1a003eeb972b8bcaa0f466e9fa91757e340f6409fed1fee5e0fde"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "27713513"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/srep34892"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1009099485"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/srep34892", 
      "https://app.dimensions.ai/details/publication/pub.1009099485"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T13:24", 
    "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_8659_00000549.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://www.nature.com/srep/2016/161007/srep34892/full/srep34892.html"
  }
]
 

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/srep34892'

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/srep34892'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/srep34892'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/srep34892'


 

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

371 TRIPLES      21 PREDICATES      98 URIs      31 LITERALS      19 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/srep34892 schema:about N1736aff92ee44861bae0a00dfa1c3c91
2 N23c60c73998842f999d2ed7d9de69b09
3 N24e45e6a424e411eb63763c290ecd512
4 N693872814e254376bae86e9b43a2d04a
5 N6a7b625b5dcc4746842e1ce07bc974d7
6 N7b1fc4f1f945450ca7f229496cbb4125
7 Nb19431c3fb2a4fabb86af91351925adc
8 Nb52d10e926094348a81be31ad1419030
9 Nc25fd9f668054794b1a024bbdf24d325
10 Nefaf655a25aa4c7288b54da30e749c6d
11 anzsrc-for:06
12 anzsrc-for:0604
13 schema:author N16067030bfe34afe864648abe5e5362d
14 schema:citation sg:pub.10.1007/s00335-015-9583-x
15 sg:pub.10.1007/s00438-014-0882-9
16 sg:pub.10.1007/s00438-014-0952-z
17 sg:pub.10.1007/s00441-014-1885-x
18 sg:pub.10.1038/nature10398
19 sg:pub.10.1038/nature11233
20 sg:pub.10.1038/nature11247
21 sg:pub.10.1038/nature13182
22 sg:pub.10.1038/nature13992
23 sg:pub.10.1038/nbt.1633
24 sg:pub.10.1038/nbt.2596
25 sg:pub.10.1038/nbt.3122
26 sg:pub.10.1038/ncb437
27 sg:pub.10.1038/ng.3192
28 sg:pub.10.1038/ng.703
29 sg:pub.10.1038/nmeth.1470
30 sg:pub.10.1038/nmeth.1923
31 sg:pub.10.1038/nmeth.3317
32 sg:pub.10.1038/nprot.2012.016
33 sg:pub.10.1038/nrg2484
34 sg:pub.10.1038/nrg3642
35 sg:pub.10.1038/srep23700
36 sg:pub.10.1186/1471-2105-13-s6-s4
37 sg:pub.10.1186/1471-2164-13-455
38 https://doi.org/10.1016/j.cell.2007.02.016
39 https://doi.org/10.1016/j.cell.2008.01.015
40 https://doi.org/10.1016/j.cell.2013.02.016
41 https://doi.org/10.1016/j.devcel.2012.12.012
42 https://doi.org/10.1016/j.molcel.2011.08.018
43 https://doi.org/10.1016/j.stem.2013.03.003
44 https://doi.org/10.1016/j.stem.2014.05.014
45 https://doi.org/10.1016/j.stem.2015.03.007
46 https://doi.org/10.1073/pnas.0506580102
47 https://doi.org/10.1093/bfgp/elv024
48 https://doi.org/10.1093/bib/bbv033
49 https://doi.org/10.1093/bioinformatics/bti736
50 https://doi.org/10.1093/nar/gkp335
51 https://doi.org/10.1093/nar/gkt006
52 https://doi.org/10.1093/nar/gkt818
53 https://doi.org/10.1093/nar/gkt997
54 https://doi.org/10.1093/nar/gku325
55 https://doi.org/10.1093/nar/gkv1157
56 https://doi.org/10.1101/gr.074906.107
57 https://doi.org/10.1101/gr.078378.108
58 https://doi.org/10.1101/gr.132159.111
59 https://doi.org/10.1101/gr.139618.112
60 https://doi.org/10.1101/gr.156232.113
61 https://doi.org/10.1101/gr.181974.114
62 https://doi.org/10.1109/tmi.2014.2317520
63 https://doi.org/10.1109/tnnls.2014.2342533
64 https://doi.org/10.1155/2011/875309
65 https://doi.org/10.1155/2014/416323
66 https://doi.org/10.1242/dev.105858
67 https://doi.org/10.1242/dev.116996
68 https://doi.org/10.1242/dmm.000232
69 https://doi.org/10.1371/journal.pone.0071152
70 https://doi.org/10.1371/journal.pone.0109443
71 https://doi.org/10.2174/13892029113149990005
72 https://doi.org/10.7554/elife.02046
73 schema:datePublished 2016-12
74 schema:datePublishedReg 2016-12-01
75 schema:description As the regulatory factors, lncRNAs play critical roles in embryonic stem cells. And lincRNAs are most widely studied lncRNAs, however, there might still might exist a large member of uncovered lncRNAs. In this study, we constructed the de novo assembly of transcriptome to detect 6,701 putative long intergenic non-coding transcripts (lincRNAs) expressed in mouse embryonic stem cells (ESCs), which might be incomplete with the lack coverage of 5' ends assessed by CAGE peaks. Comparing the TSS proximal regions between the known lincRNAs and their closet protein coding transcripts, our results revealed that the lincRNA TSS proximal regions are associated with the characteristic genomic and epigenetic features. Subsequently, 1,293 lincRNAs were corrected at their 5' ends using the putative lincRNA TSS regions predicted by the TSS proximal region prediction model based on genomic and epigenetic features. Finally, 43 putative lincRNAs were annotated by Gene Ontology terms. In conclusion, this work provides a novel catalog of mouse ESCs-expressed lincRNAs with the relatively complete transcript length, which might be useful for the investigation of transcriptional and post-transcriptional regulation of lincRNA in mouse ESCs and even mammalian development.
76 schema:genre research_article
77 schema:inLanguage en
78 schema:isAccessibleForFree true
79 schema:isPartOf N3ea5d244c89045aba73ec279e0952906
80 Ne5c3c96a1ae24cc38f81150fc33fca18
81 sg:journal.1045337
82 schema:name Computational identification of putative lincRNAs in mouse embryonic stem cell
83 schema:pagination 34892
84 schema:productId N0cc8c3be235444bf86897ff25b01dd8d
85 N569163829c5444a1a948662298bc56ef
86 N67cdec76f209475cade18b50d705d740
87 N807e9dffd61741cb986726a469eb0c3b
88 N80c1e333824f424291a35bacf31743a7
89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009099485
90 https://doi.org/10.1038/srep34892
91 schema:sdDatePublished 2019-04-10T13:24
92 schema:sdLicense https://scigraph.springernature.com/explorer/license/
93 schema:sdPublisher N756e3b02c6fb4f1cab674814b6b981c8
94 schema:url http://www.nature.com/srep/2016/161007/srep34892/full/srep34892.html
95 sgo:license sg:explorer/license/
96 sgo:sdDataset articles
97 rdf:type schema:ScholarlyArticle
98 N0cc8c3be235444bf86897ff25b01dd8d schema:name nlm_unique_id
99 schema:value 101563288
100 rdf:type schema:PropertyValue
101 N16067030bfe34afe864648abe5e5362d rdf:first sg:person.01021140626.25
102 rdf:rest N66678ef3f04d4909af158da70039e8cd
103 N1736aff92ee44861bae0a00dfa1c3c91 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Animals
105 rdf:type schema:DefinedTerm
106 N23c60c73998842f999d2ed7d9de69b09 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Mouse Embryonic Stem Cells
108 rdf:type schema:DefinedTerm
109 N24e45e6a424e411eb63763c290ecd512 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
110 schema:name Gene Expression Regulation, Developmental
111 rdf:type schema:DefinedTerm
112 N3ea5d244c89045aba73ec279e0952906 schema:volumeNumber 6
113 rdf:type schema:PublicationVolume
114 N4455da8ed2bc4722be4ae8f041ccfdf6 rdf:first sg:person.0753025426.94
115 rdf:rest N6fd79aa43ced48889959763bfa7f78bc
116 N569163829c5444a1a948662298bc56ef schema:name readcube_id
117 schema:value 2b59fcae5ab1a003eeb972b8bcaa0f466e9fa91757e340f6409fed1fee5e0fde
118 rdf:type schema:PropertyValue
119 N66678ef3f04d4909af158da70039e8cd rdf:first sg:person.010552444221.76
120 rdf:rest N4455da8ed2bc4722be4ae8f041ccfdf6
121 N67cdec76f209475cade18b50d705d740 schema:name pubmed_id
122 schema:value 27713513
123 rdf:type schema:PropertyValue
124 N693872814e254376bae86e9b43a2d04a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
125 schema:name Machine Learning
126 rdf:type schema:DefinedTerm
127 N69eade8751af4cd19dbecbb21e92d3a8 rdf:first sg:person.01140440275.43
128 rdf:rest Na91e6512dd5c45d1b8accc0a55243f0e
129 N6a7b625b5dcc4746842e1ce07bc974d7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Models, Genetic
131 rdf:type schema:DefinedTerm
132 N6b3dc927356d4c448fad7c76b57f5d65 rdf:first sg:person.01131113612.76
133 rdf:rest rdf:nil
134 N6fd79aa43ced48889959763bfa7f78bc rdf:first sg:person.01235756516.88
135 rdf:rest N69eade8751af4cd19dbecbb21e92d3a8
136 N756e3b02c6fb4f1cab674814b6b981c8 schema:name Springer Nature - SN SciGraph project
137 rdf:type schema:Organization
138 N7b1fc4f1f945450ca7f229496cbb4125 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Chromatin
140 rdf:type schema:DefinedTerm
141 N807e9dffd61741cb986726a469eb0c3b schema:name dimensions_id
142 schema:value pub.1009099485
143 rdf:type schema:PropertyValue
144 N80c1e333824f424291a35bacf31743a7 schema:name doi
145 schema:value 10.1038/srep34892
146 rdf:type schema:PropertyValue
147 N9b51b807df954d0db72a673d1bf12ad8 rdf:first sg:person.01334631563.02
148 rdf:rest Nd2065ff018f3406e98582e7cc33590e7
149 Na91e6512dd5c45d1b8accc0a55243f0e rdf:first sg:person.0634554317.27
150 rdf:rest N9b51b807df954d0db72a673d1bf12ad8
151 Nb19431c3fb2a4fabb86af91351925adc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
152 schema:name RNA, Long Noncoding
153 rdf:type schema:DefinedTerm
154 Nb52d10e926094348a81be31ad1419030 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Epigenesis, Genetic
156 rdf:type schema:DefinedTerm
157 Nc25fd9f668054794b1a024bbdf24d325 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Mice
159 rdf:type schema:DefinedTerm
160 Nd2065ff018f3406e98582e7cc33590e7 rdf:first sg:person.01251615626.81
161 rdf:rest N6b3dc927356d4c448fad7c76b57f5d65
162 Ne5c3c96a1ae24cc38f81150fc33fca18 schema:issueNumber 1
163 rdf:type schema:PublicationIssue
164 Nefaf655a25aa4c7288b54da30e749c6d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
165 schema:name Transcription Initiation Site
166 rdf:type schema:DefinedTerm
167 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
168 schema:name Biological Sciences
169 rdf:type schema:DefinedTerm
170 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
171 schema:name Genetics
172 rdf:type schema:DefinedTerm
173 sg:journal.1045337 schema:issn 2045-2322
174 schema:name Scientific Reports
175 rdf:type schema:Periodical
176 sg:person.01021140626.25 schema:affiliation https://www.grid.ac/institutes/grid.19373.3f
177 schema:familyName Liu
178 schema:givenName Hui
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021140626.25
180 rdf:type schema:Person
181 sg:person.010552444221.76 schema:affiliation https://www.grid.ac/institutes/grid.39382.33
182 schema:familyName Lyu
183 schema:givenName Jie
184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010552444221.76
185 rdf:type schema:Person
186 sg:person.01131113612.76 schema:affiliation https://www.grid.ac/institutes/grid.19373.3f
187 schema:familyName Wu
188 schema:givenName Qiong
189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01131113612.76
190 rdf:type schema:Person
191 sg:person.01140440275.43 schema:affiliation https://www.grid.ac/institutes/grid.19373.3f
192 schema:familyName Guo
193 schema:givenName Jing
194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01140440275.43
195 rdf:type schema:Person
196 sg:person.01235756516.88 schema:affiliation https://www.grid.ac/institutes/grid.19373.3f
197 schema:familyName Gao
198 schema:givenName Yang
199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01235756516.88
200 rdf:type schema:Person
201 sg:person.01251615626.81 schema:affiliation https://www.grid.ac/institutes/grid.410736.7
202 schema:familyName Zhang
203 schema:givenName Yan
204 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01251615626.81
205 rdf:type schema:Person
206 sg:person.01334631563.02 schema:affiliation https://www.grid.ac/institutes/grid.19373.3f
207 schema:familyName Han
208 schema:givenName Zhengbin
209 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334631563.02
210 rdf:type schema:Person
211 sg:person.0634554317.27 schema:affiliation https://www.grid.ac/institutes/grid.19373.3f
212 schema:familyName He
213 schema:givenName Hongjuan
214 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0634554317.27
215 rdf:type schema:Person
216 sg:person.0753025426.94 schema:affiliation https://www.grid.ac/institutes/grid.410736.7
217 schema:familyName Liu
218 schema:givenName Hongbo
219 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0753025426.94
220 rdf:type schema:Person
221 sg:pub.10.1007/s00335-015-9583-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011692857
222 https://doi.org/10.1007/s00335-015-9583-x
223 rdf:type schema:CreativeWork
224 sg:pub.10.1007/s00438-014-0882-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010544024
225 https://doi.org/10.1007/s00438-014-0882-9
226 rdf:type schema:CreativeWork
227 sg:pub.10.1007/s00438-014-0952-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1029950376
228 https://doi.org/10.1007/s00438-014-0952-z
229 rdf:type schema:CreativeWork
230 sg:pub.10.1007/s00441-014-1885-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1027912826
231 https://doi.org/10.1007/s00441-014-1885-x
232 rdf:type schema:CreativeWork
233 sg:pub.10.1038/nature10398 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018204822
234 https://doi.org/10.1038/nature10398
235 rdf:type schema:CreativeWork
236 sg:pub.10.1038/nature11233 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003047559
237 https://doi.org/10.1038/nature11233
238 rdf:type schema:CreativeWork
239 sg:pub.10.1038/nature11247 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029065430
240 https://doi.org/10.1038/nature11247
241 rdf:type schema:CreativeWork
242 sg:pub.10.1038/nature13182 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029370855
243 https://doi.org/10.1038/nature13182
244 rdf:type schema:CreativeWork
245 sg:pub.10.1038/nature13992 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036662703
246 https://doi.org/10.1038/nature13992
247 rdf:type schema:CreativeWork
248 sg:pub.10.1038/nbt.1633 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025339324
249 https://doi.org/10.1038/nbt.1633
250 rdf:type schema:CreativeWork
251 sg:pub.10.1038/nbt.2596 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048926875
252 https://doi.org/10.1038/nbt.2596
253 rdf:type schema:CreativeWork
254 sg:pub.10.1038/nbt.3122 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045760294
255 https://doi.org/10.1038/nbt.3122
256 rdf:type schema:CreativeWork
257 sg:pub.10.1038/ncb437 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023498683
258 https://doi.org/10.1038/ncb437
259 rdf:type schema:CreativeWork
260 sg:pub.10.1038/ng.3192 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028060819
261 https://doi.org/10.1038/ng.3192
262 rdf:type schema:CreativeWork
263 sg:pub.10.1038/ng.703 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043122239
264 https://doi.org/10.1038/ng.703
265 rdf:type schema:CreativeWork
266 sg:pub.10.1038/nmeth.1470 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047181882
267 https://doi.org/10.1038/nmeth.1470
268 rdf:type schema:CreativeWork
269 sg:pub.10.1038/nmeth.1923 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006541515
270 https://doi.org/10.1038/nmeth.1923
271 rdf:type schema:CreativeWork
272 sg:pub.10.1038/nmeth.3317 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005140994
273 https://doi.org/10.1038/nmeth.3317
274 rdf:type schema:CreativeWork
275 sg:pub.10.1038/nprot.2012.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030124536
276 https://doi.org/10.1038/nprot.2012.016
277 rdf:type schema:CreativeWork
278 sg:pub.10.1038/nrg2484 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030687647
279 https://doi.org/10.1038/nrg2484
280 rdf:type schema:CreativeWork
281 sg:pub.10.1038/nrg3642 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010746394
282 https://doi.org/10.1038/nrg3642
283 rdf:type schema:CreativeWork
284 sg:pub.10.1038/srep23700 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034825005
285 https://doi.org/10.1038/srep23700
286 rdf:type schema:CreativeWork
287 sg:pub.10.1186/1471-2105-13-s6-s4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008968188
288 https://doi.org/10.1186/1471-2105-13-s6-s4
289 rdf:type schema:CreativeWork
290 sg:pub.10.1186/1471-2164-13-455 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024040876
291 https://doi.org/10.1186/1471-2164-13-455
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1016/j.cell.2007.02.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027946228
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1016/j.cell.2008.01.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012430287
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1016/j.cell.2013.02.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043978712
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1016/j.devcel.2012.12.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008652964
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1016/j.molcel.2011.08.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017411851
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1016/j.stem.2013.03.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021983761
304 rdf:type schema:CreativeWork
305 https://doi.org/10.1016/j.stem.2014.05.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049735919
306 rdf:type schema:CreativeWork
307 https://doi.org/10.1016/j.stem.2015.03.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018793531
308 rdf:type schema:CreativeWork
309 https://doi.org/10.1073/pnas.0506580102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037705714
310 rdf:type schema:CreativeWork
311 https://doi.org/10.1093/bfgp/elv024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059412963
312 rdf:type schema:CreativeWork
313 https://doi.org/10.1093/bib/bbv033 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059413086
314 rdf:type schema:CreativeWork
315 https://doi.org/10.1093/bioinformatics/bti736 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036795811
316 rdf:type schema:CreativeWork
317 https://doi.org/10.1093/nar/gkp335 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007915246
318 rdf:type schema:CreativeWork
319 https://doi.org/10.1093/nar/gkt006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004840937
320 rdf:type schema:CreativeWork
321 https://doi.org/10.1093/nar/gkt818 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039201808
322 rdf:type schema:CreativeWork
323 https://doi.org/10.1093/nar/gkt997 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036657357
324 rdf:type schema:CreativeWork
325 https://doi.org/10.1093/nar/gku325 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002238968
326 rdf:type schema:CreativeWork
327 https://doi.org/10.1093/nar/gkv1157 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037937986
328 rdf:type schema:CreativeWork
329 https://doi.org/10.1101/gr.074906.107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042580562
330 rdf:type schema:CreativeWork
331 https://doi.org/10.1101/gr.078378.108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048137976
332 rdf:type schema:CreativeWork
333 https://doi.org/10.1101/gr.132159.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013862605
334 rdf:type schema:CreativeWork
335 https://doi.org/10.1101/gr.139618.112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020375059
336 rdf:type schema:CreativeWork
337 https://doi.org/10.1101/gr.156232.113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013427894
338 rdf:type schema:CreativeWork
339 https://doi.org/10.1101/gr.181974.114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033420430
340 rdf:type schema:CreativeWork
341 https://doi.org/10.1109/tmi.2014.2317520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061696289
342 rdf:type schema:CreativeWork
343 https://doi.org/10.1109/tnnls.2014.2342533 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061718648
344 rdf:type schema:CreativeWork
345 https://doi.org/10.1155/2011/875309 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006345668
346 rdf:type schema:CreativeWork
347 https://doi.org/10.1155/2014/416323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014812994
348 rdf:type schema:CreativeWork
349 https://doi.org/10.1242/dev.105858 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028460790
350 rdf:type schema:CreativeWork
351 https://doi.org/10.1242/dev.116996 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047207739
352 rdf:type schema:CreativeWork
353 https://doi.org/10.1242/dmm.000232 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029924862
354 rdf:type schema:CreativeWork
355 https://doi.org/10.1371/journal.pone.0071152 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035017475
356 rdf:type schema:CreativeWork
357 https://doi.org/10.1371/journal.pone.0109443 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045775109
358 rdf:type schema:CreativeWork
359 https://doi.org/10.2174/13892029113149990005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069178678
360 rdf:type schema:CreativeWork
361 https://doi.org/10.7554/elife.02046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015743913
362 rdf:type schema:CreativeWork
363 https://www.grid.ac/institutes/grid.19373.3f schema:alternateName Harbin Institute of Technology
364 schema:name School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China.
365 rdf:type schema:Organization
366 https://www.grid.ac/institutes/grid.39382.33 schema:alternateName Baylor College of Medicine
367 schema:name Dan L. Duncan Cancer Center, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, 77030, USA.
368 rdf:type schema:Organization
369 https://www.grid.ac/institutes/grid.410736.7 schema:alternateName Harbin Medical University
370 schema:name College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
371 rdf:type schema:Organization
 




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


...