Sequence homology in eukaryotes (SHOE): interactive visual tool for promoter analysis View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Natalia Polouliakh, Paul Horton, Kazuhiro Shibanai, Kodai Takata, Vanessa Ludwig, Samik Ghosh, Hiroaki Kitano

ABSTRACT

BACKGROUND: Microarray and DNA-sequencing based technologies continue to produce enormous amounts of data on gene expression. This data has great potential to illuminate our understanding of biology and medicine, but the data alone is of limited value without computational tools to allow human investigators to visualize and interpret it in the context of their problem of interest. RESULTS: We created a web server called SHOE that provides an interactive, visual presentation of the available evidence of transcriptional regulation and gene co-expression to facilitate its exploration and interpretation. SHOE predicts the likely transcription factor binding sites in orthologous promoters of humans, mice, and rats using the combined information of 1) transcription factor binding preferences (position-specific scoring matrix (PSSM) libraries such as Transfac32, Jaspar, HOCOMOCO, ChIP-seq, SELEX, PBM, and iPS-reprogramming factor), 2) evolutionary conservation of putative binding sites in orthologous promoters, and 3) co-expression tendencies of gene pairs based on 1,714 normal human cells selected from the Gene Expression Omnibus Database. CONCLUSION: SHOE enables users to explore potential interactions between transcription factors and target genes via multiple data views, discover transcription factor binding motifs on top of gene co-expression, and visualize genes as a network of gene and transcription factors on its native gadget GeneViz, the CellDesigner pathway analyzer, and the Reactome database to search the pathways involved. As we demonstrate here when using the CREB1 and Nf-κB datasets, SHOE can reliably identify experimentally verified interactions and predict plausible novel ones, yielding new biological insights into the gene regulatory mechanisms involved. SHOE comes with a manual describing how to run it on a local PC or via the Garuda platform ( www.garuda-alliance.org ), where it joins other popular gadgets such as the CellDesigner pathway analyzer and the Reactome database, as part of analysis workflows to meet the growing needs of molecular biologists and medical researchers. SHOE is available from the following URL http://ec2-54-150-223-65.ap-northeast-1.compute.amazonaws.com A video demonstration of SHOE can be found here: https://www.youtube.com/watch?v=qARinNb9NtE. More... »

PAGES

715

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12864-018-5101-3

DOI

http://dx.doi.org/10.1186/s12864-018-5101-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107280405

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30261835


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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Systems Biology Institute", 
          "id": "https://www.grid.ac/institutes/grid.452864.9", 
          "name": [
            "Sony Computer Science Laboratories Inc., 3-14-13 Higashigotanda, Shinagawa-ku, 141-0022, Tokyo, Japan", 
            "Department of Ophthalmology and Visual Sciences, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City, 236-0004, Yokohama, Japan", 
            "Systems Biology Institute, 5-6-9 Shirokanedai, Minato-ku, 108-0071, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Polouliakh", 
        "givenName": "Natalia", 
        "id": "sg:person.01001220301.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01001220301.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Institute of Advanced Industrial Science and Technology", 
          "id": "https://www.grid.ac/institutes/grid.208504.b", 
          "name": [
            "AIST, Artificial Intelligence Research Center, 2-4-7 Aomi, Koto-ku, 135-0064, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Horton", 
        "givenName": "Paul", 
        "id": "sg:person.01132003156.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01132003156.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.32197.3e", 
          "name": [
            "Department of Computer Science, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shibanai", 
        "givenName": "Kazuhiro", 
        "id": "sg:person.016666666470.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016666666470.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.32197.3e", 
          "name": [
            "Department of Computer Science, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takata", 
        "givenName": "Kodai", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Swiss Federal Institute of Technology in Zurich", 
          "id": "https://www.grid.ac/institutes/grid.5801.c", 
          "name": [
            "Department of Biology, ETH Zurich, Wolfgang-Pauli-Strasse 27, 8093, Zurich, Switzerland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ludwig", 
        "givenName": "Vanessa", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Systems Biology Institute", 
          "id": "https://www.grid.ac/institutes/grid.452864.9", 
          "name": [
            "Systems Biology Institute, 5-6-9 Shirokanedai, Minato-ku, 108-0071, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ghosh", 
        "givenName": "Samik", 
        "id": "sg:person.01245175236.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01245175236.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Systems Biology Institute", 
          "id": "https://www.grid.ac/institutes/grid.452864.9", 
          "name": [
            "Sony Computer Science Laboratories Inc., 3-14-13 Higashigotanda, Shinagawa-ku, 141-0022, Tokyo, Japan", 
            "Systems Biology Institute, 5-6-9 Shirokanedai, Minato-ku, 108-0071, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kitano", 
        "givenName": "Hiroaki", 
        "id": "sg:person.01355755204.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01355755204.11"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/0471250953.bi0807s7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000053539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.104216.109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000604285"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbrc.2014.06.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000937666"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.cdd.4401737", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001236310", 
          "https://doi.org/10.1038/sj.cdd.4401737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.cdd.4401737", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001236310", 
          "https://doi.org/10.1038/sj.cdd.4401737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmbi.1999.2752", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001655546"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btm462", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003107290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkm415", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003264848"
        ], 
        "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.bioeng.2007.03.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009313636"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1090100", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009574243"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg3096", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011269644", 
          "https://doi.org/10.1038/nrg3096"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2010-11-5-r53", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012013843", 
          "https://doi.org/10.1186/gb-2010-11-5-r53"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2164-7-64", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012493227", 
          "https://doi.org/10.1186/1471-2164-7-64"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2014.10.050", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013710164"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2014.10.050", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013710164"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1074/jbc.m112.447318", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015168851"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molimm.2011.05.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015786912"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gki420", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016856957"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/onc.2015.399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017384962", 
          "https://doi.org/10.1038/onc.2015.399"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0057766", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018269824"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bfgp/elp014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019553702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bfgp/elp014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019553702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkv1249", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019852236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1042/bj20080476", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023394254"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1042/bj20080476", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023394254"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2008-9-s1-s4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024435781", 
          "https://doi.org/10.1186/gb-2008-9-s1-s4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0076-6879(02)50979-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024630464"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(82)90398-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025042064"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/mcb.10.4.1498", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025930926"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/0471250953.bi0203s00", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026183986"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1074/jbc.272.47.29468", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026237241"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1475-4924-2-13", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029375403", 
          "https://doi.org/10.1186/1475-4924-2-13"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4049/jimmunol.178.11.7097", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030549107"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/15.7.563", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030639875"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt1053", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030939237", 
          "https://doi.org/10.1038/nbt1053"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt1053", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030939237", 
          "https://doi.org/10.1038/nbt1053"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkh012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031148109"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fphys.2013.00007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031299318"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/24.1.238", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031417336"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2407-8-264", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031823767", 
          "https://doi.org/10.1186/1471-2407-8-264"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gki022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033237811"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00251-003-0597-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033781578", 
          "https://doi.org/10.1007/s00251-003-0597-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.529803", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033963838"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/jcs.02445", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034514170"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0046928", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035936855"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.aca.2008.07.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035973233"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gku1080", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035984294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00384-007-0396-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037191027", 
          "https://doi.org/10.1007/s00384-007-0396-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00384-007-0396-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037191027", 
          "https://doi.org/10.1007/s00384-007-0396-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gku1045", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037369796"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkl995", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039365866"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbrc.2008.03.136", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041372035"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2164-13-s1-s3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041782988", 
          "https://doi.org/10.1186/1471-2164-13-s1-s3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02289162", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043322383", 
          "https://doi.org/10.1007/bf02289162"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02289162", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043322383", 
          "https://doi.org/10.1007/bf02289162"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2004-5-10-r73", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043495139", 
          "https://doi.org/10.1186/gb-2004-5-10-r73"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbrc.2015.11.113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043510001"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/cshperspect.a001271", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044571076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.225502", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045742587"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1084/jem.181.4.1459", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049377611"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1084/jem.181.4.1459", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049377611"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature03441", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050742226", 
          "https://doi.org/10.1038/nature03441"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature03441", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050742226", 
          "https://doi.org/10.1038/nature03441"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cellsig.2005.08.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051918495"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cellsig.2005.08.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051918495"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbrc.2004.01.025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051943115"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12864-015-1511-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053563638", 
          "https://doi.org/10.1186/s12864-015-1511-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12864-015-1511-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053563638", 
          "https://doi.org/10.1186/s12864-015-1511-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1089/153623103322452378", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059215054"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tcbb.2009.25", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061540706"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.8211139", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062653653"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1142/s0219720006001849", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063004674"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/mend.14.8.0506", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064332034"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1074787296", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077478443", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1082560041", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/j.1460-2075.1996.tb00706.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082902155"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1083068642", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1142/9789814447362_0014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1096039980"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "BACKGROUND: Microarray and DNA-sequencing based technologies continue to produce enormous amounts of data on gene expression. This data has great potential to illuminate our understanding of biology and medicine, but the data alone is of limited value without computational tools to allow human investigators to visualize and interpret it in the context of their problem of interest.\nRESULTS: We created a web server called SHOE that provides an interactive, visual presentation of the available evidence of transcriptional regulation and gene co-expression to facilitate its exploration and interpretation. SHOE predicts the likely transcription factor binding sites in orthologous promoters of humans, mice, and rats using the combined information of 1) transcription factor binding preferences (position-specific scoring matrix (PSSM) libraries such as Transfac32, Jaspar, HOCOMOCO, ChIP-seq, SELEX, PBM, and iPS-reprogramming factor), 2) evolutionary conservation of putative binding sites in orthologous promoters, and 3) co-expression tendencies of gene pairs based on 1,714 normal human cells selected from the Gene Expression Omnibus Database.\nCONCLUSION: SHOE enables users to explore potential interactions between transcription factors and target genes via multiple data views, discover transcription factor binding motifs on top of gene co-expression, and visualize genes as a network of gene and transcription factors on its native gadget GeneViz, the CellDesigner pathway analyzer, and the Reactome database to search the pathways involved. As we demonstrate here when using the CREB1 and Nf-\u03baB datasets, SHOE can reliably identify experimentally verified interactions and predict plausible novel ones, yielding new biological insights into the gene regulatory mechanisms involved. SHOE comes with a manual describing how to run it on a local PC or via the Garuda platform ( www.garuda-alliance.org ), where it joins other popular gadgets such as the CellDesigner pathway analyzer and the Reactome database, as part of analysis workflows to meet the growing needs of molecular biologists and medical researchers. SHOE is available from the following URL http://ec2-54-150-223-65.ap-northeast-1.compute.amazonaws.com A video demonstration of SHOE can be found here: https://www.youtube.com/watch?v=qARinNb9NtE.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s12864-018-5101-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1023790", 
        "issn": [
          "1471-2164"
        ], 
        "name": "BMC Genomics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "19"
      }
    ], 
    "name": "Sequence homology in eukaryotes (SHOE): interactive visual tool for promoter analysis", 
    "pagination": "715", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "15d06c7d7651debb67d0cf76b04ac7125d77a6eea1f6a66d0c864db3215c7704"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30261835"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100965258"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12864-018-5101-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1107280405"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12864-018-5101-3", 
      "https://app.dimensions.ai/details/publication/pub.1107280405"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T23:31", 
    "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_8693_00000548.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs12864-018-5101-3"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12864-018-5101-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12864-018-5101-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12864-018-5101-3'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12864-018-5101-3'


 

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

338 TRIPLES      21 PREDICATES      98 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12864-018-5101-3 schema:about anzsrc-for:06
2 anzsrc-for:0604
3 schema:author Nc614bdba761d422b8f304cde93c9666a
4 schema:citation sg:pub.10.1007/bf02289162
5 sg:pub.10.1007/s00251-003-0597-2
6 sg:pub.10.1007/s00384-007-0396-6
7 sg:pub.10.1038/nature03441
8 sg:pub.10.1038/nbt1053
9 sg:pub.10.1038/nrg3096
10 sg:pub.10.1038/onc.2015.399
11 sg:pub.10.1038/sj.cdd.4401737
12 sg:pub.10.1186/1471-2164-13-s1-s3
13 sg:pub.10.1186/1471-2164-7-64
14 sg:pub.10.1186/1471-2407-8-264
15 sg:pub.10.1186/1475-4924-2-13
16 sg:pub.10.1186/gb-2004-5-10-r73
17 sg:pub.10.1186/gb-2008-9-s1-s4
18 sg:pub.10.1186/gb-2010-11-5-r53
19 sg:pub.10.1186/s12864-015-1511-7
20 https://app.dimensions.ai/details/publication/pub.1074787296
21 https://app.dimensions.ai/details/publication/pub.1077478443
22 https://app.dimensions.ai/details/publication/pub.1082560041
23 https://app.dimensions.ai/details/publication/pub.1083068642
24 https://doi.org/10.1002/0471250953.bi0203s00
25 https://doi.org/10.1002/0471250953.bi0807s7
26 https://doi.org/10.1002/j.1460-2075.1996.tb00706.x
27 https://doi.org/10.1006/jmbi.1999.2752
28 https://doi.org/10.1016/0022-2836(82)90398-9
29 https://doi.org/10.1016/j.aca.2008.07.006
30 https://doi.org/10.1016/j.bbrc.2004.01.025
31 https://doi.org/10.1016/j.bbrc.2008.03.136
32 https://doi.org/10.1016/j.bbrc.2014.06.006
33 https://doi.org/10.1016/j.bbrc.2015.11.113
34 https://doi.org/10.1016/j.bioeng.2007.03.001
35 https://doi.org/10.1016/j.cell.2014.10.050
36 https://doi.org/10.1016/j.cellsig.2005.08.021
37 https://doi.org/10.1016/j.molimm.2011.05.021
38 https://doi.org/10.1016/s0076-6879(02)50979-4
39 https://doi.org/10.1042/bj20080476
40 https://doi.org/10.1074/jbc.272.47.29468
41 https://doi.org/10.1074/jbc.m112.447318
42 https://doi.org/10.1084/jem.181.4.1459
43 https://doi.org/10.1089/153623103322452378
44 https://doi.org/10.1093/bfgp/elp014
45 https://doi.org/10.1093/bioinformatics/15.7.563
46 https://doi.org/10.1093/bioinformatics/btm462
47 https://doi.org/10.1093/nar/24.1.238
48 https://doi.org/10.1093/nar/gkh012
49 https://doi.org/10.1093/nar/gki022
50 https://doi.org/10.1093/nar/gki420
51 https://doi.org/10.1093/nar/gkl995
52 https://doi.org/10.1093/nar/gkm415
53 https://doi.org/10.1093/nar/gkp335
54 https://doi.org/10.1093/nar/gku1045
55 https://doi.org/10.1093/nar/gku1080
56 https://doi.org/10.1093/nar/gkv1249
57 https://doi.org/10.1101/cshperspect.a001271
58 https://doi.org/10.1101/gr.104216.109
59 https://doi.org/10.1101/gr.225502
60 https://doi.org/10.1101/gr.529803
61 https://doi.org/10.1109/tcbb.2009.25
62 https://doi.org/10.1126/science.1090100
63 https://doi.org/10.1126/science.8211139
64 https://doi.org/10.1128/mcb.10.4.1498
65 https://doi.org/10.1142/9789814447362_0014
66 https://doi.org/10.1142/s0219720006001849
67 https://doi.org/10.1210/mend.14.8.0506
68 https://doi.org/10.1242/jcs.02445
69 https://doi.org/10.1371/journal.pone.0046928
70 https://doi.org/10.1371/journal.pone.0057766
71 https://doi.org/10.3389/fphys.2013.00007
72 https://doi.org/10.4049/jimmunol.178.11.7097
73 schema:datePublished 2018-12
74 schema:datePublishedReg 2018-12-01
75 schema:description BACKGROUND: Microarray and DNA-sequencing based technologies continue to produce enormous amounts of data on gene expression. This data has great potential to illuminate our understanding of biology and medicine, but the data alone is of limited value without computational tools to allow human investigators to visualize and interpret it in the context of their problem of interest. RESULTS: We created a web server called SHOE that provides an interactive, visual presentation of the available evidence of transcriptional regulation and gene co-expression to facilitate its exploration and interpretation. SHOE predicts the likely transcription factor binding sites in orthologous promoters of humans, mice, and rats using the combined information of 1) transcription factor binding preferences (position-specific scoring matrix (PSSM) libraries such as Transfac32, Jaspar, HOCOMOCO, ChIP-seq, SELEX, PBM, and iPS-reprogramming factor), 2) evolutionary conservation of putative binding sites in orthologous promoters, and 3) co-expression tendencies of gene pairs based on 1,714 normal human cells selected from the Gene Expression Omnibus Database. CONCLUSION: SHOE enables users to explore potential interactions between transcription factors and target genes via multiple data views, discover transcription factor binding motifs on top of gene co-expression, and visualize genes as a network of gene and transcription factors on its native gadget GeneViz, the CellDesigner pathway analyzer, and the Reactome database to search the pathways involved. As we demonstrate here when using the CREB1 and Nf-κB datasets, SHOE can reliably identify experimentally verified interactions and predict plausible novel ones, yielding new biological insights into the gene regulatory mechanisms involved. SHOE comes with a manual describing how to run it on a local PC or via the Garuda platform ( www.garuda-alliance.org ), where it joins other popular gadgets such as the CellDesigner pathway analyzer and the Reactome database, as part of analysis workflows to meet the growing needs of molecular biologists and medical researchers. SHOE is available from the following URL http://ec2-54-150-223-65.ap-northeast-1.compute.amazonaws.com A video demonstration of SHOE can be found here: https://www.youtube.com/watch?v=qARinNb9NtE.
76 schema:genre research_article
77 schema:inLanguage en
78 schema:isAccessibleForFree true
79 schema:isPartOf Nb1386136410c42f0b56aa5ac7ef57344
80 Nb30e557ccfc74b888fe890ba29922d81
81 sg:journal.1023790
82 schema:name Sequence homology in eukaryotes (SHOE): interactive visual tool for promoter analysis
83 schema:pagination 715
84 schema:productId N2bd3ddd3edd84269acc51ae1a0eea65a
85 N4052ff17bfdc4a3e8a53c07376f334ca
86 N7a394f75770644ea8b4d2cd4812751b4
87 N85b3012b57c84e3994c192600c818655
88 Nc013f1cef4dd4fc9b0785b0268b20fc9
89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107280405
90 https://doi.org/10.1186/s12864-018-5101-3
91 schema:sdDatePublished 2019-04-10T23:31
92 schema:sdLicense https://scigraph.springernature.com/explorer/license/
93 schema:sdPublisher N84db5c42be7b4f0792e0b7bdba938318
94 schema:url https://link.springer.com/10.1186%2Fs12864-018-5101-3
95 sgo:license sg:explorer/license/
96 sgo:sdDataset articles
97 rdf:type schema:ScholarlyArticle
98 N09ee4a249aa641268f23eb6188612fcb schema:affiliation https://www.grid.ac/institutes/grid.5801.c
99 schema:familyName Ludwig
100 schema:givenName Vanessa
101 rdf:type schema:Person
102 N1e23c9911e814cad96043ff815289f8e rdf:first N09ee4a249aa641268f23eb6188612fcb
103 rdf:rest N48dde35d24a1468397963750444474ed
104 N212a7d1fed2c418f8d8ecac703613b49 rdf:first sg:person.01132003156.52
105 rdf:rest N9be98e6594a64b4084b4edfb953b677c
106 N2bd3ddd3edd84269acc51ae1a0eea65a schema:name doi
107 schema:value 10.1186/s12864-018-5101-3
108 rdf:type schema:PropertyValue
109 N2f58f5af74014182bd245d1025701fb6 rdf:first sg:person.01355755204.11
110 rdf:rest rdf:nil
111 N4052ff17bfdc4a3e8a53c07376f334ca schema:name nlm_unique_id
112 schema:value 100965258
113 rdf:type schema:PropertyValue
114 N48dde35d24a1468397963750444474ed rdf:first sg:person.01245175236.29
115 rdf:rest N2f58f5af74014182bd245d1025701fb6
116 N4e38948a0568425fb290c3cfe7a1c6f1 rdf:first N6c33760131374e84b70cfb3890edc710
117 rdf:rest N1e23c9911e814cad96043ff815289f8e
118 N6c33760131374e84b70cfb3890edc710 schema:affiliation https://www.grid.ac/institutes/grid.32197.3e
119 schema:familyName Takata
120 schema:givenName Kodai
121 rdf:type schema:Person
122 N7a394f75770644ea8b4d2cd4812751b4 schema:name pubmed_id
123 schema:value 30261835
124 rdf:type schema:PropertyValue
125 N84db5c42be7b4f0792e0b7bdba938318 schema:name Springer Nature - SN SciGraph project
126 rdf:type schema:Organization
127 N85b3012b57c84e3994c192600c818655 schema:name readcube_id
128 schema:value 15d06c7d7651debb67d0cf76b04ac7125d77a6eea1f6a66d0c864db3215c7704
129 rdf:type schema:PropertyValue
130 N9be98e6594a64b4084b4edfb953b677c rdf:first sg:person.016666666470.04
131 rdf:rest N4e38948a0568425fb290c3cfe7a1c6f1
132 Nb1386136410c42f0b56aa5ac7ef57344 schema:issueNumber 1
133 rdf:type schema:PublicationIssue
134 Nb30e557ccfc74b888fe890ba29922d81 schema:volumeNumber 19
135 rdf:type schema:PublicationVolume
136 Nc013f1cef4dd4fc9b0785b0268b20fc9 schema:name dimensions_id
137 schema:value pub.1107280405
138 rdf:type schema:PropertyValue
139 Nc614bdba761d422b8f304cde93c9666a rdf:first sg:person.01001220301.92
140 rdf:rest N212a7d1fed2c418f8d8ecac703613b49
141 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
142 schema:name Biological Sciences
143 rdf:type schema:DefinedTerm
144 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
145 schema:name Genetics
146 rdf:type schema:DefinedTerm
147 sg:journal.1023790 schema:issn 1471-2164
148 schema:name BMC Genomics
149 rdf:type schema:Periodical
150 sg:person.01001220301.92 schema:affiliation https://www.grid.ac/institutes/grid.452864.9
151 schema:familyName Polouliakh
152 schema:givenName Natalia
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01001220301.92
154 rdf:type schema:Person
155 sg:person.01132003156.52 schema:affiliation https://www.grid.ac/institutes/grid.208504.b
156 schema:familyName Horton
157 schema:givenName Paul
158 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01132003156.52
159 rdf:type schema:Person
160 sg:person.01245175236.29 schema:affiliation https://www.grid.ac/institutes/grid.452864.9
161 schema:familyName Ghosh
162 schema:givenName Samik
163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01245175236.29
164 rdf:type schema:Person
165 sg:person.01355755204.11 schema:affiliation https://www.grid.ac/institutes/grid.452864.9
166 schema:familyName Kitano
167 schema:givenName Hiroaki
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01355755204.11
169 rdf:type schema:Person
170 sg:person.016666666470.04 schema:affiliation https://www.grid.ac/institutes/grid.32197.3e
171 schema:familyName Shibanai
172 schema:givenName Kazuhiro
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016666666470.04
174 rdf:type schema:Person
175 sg:pub.10.1007/bf02289162 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043322383
176 https://doi.org/10.1007/bf02289162
177 rdf:type schema:CreativeWork
178 sg:pub.10.1007/s00251-003-0597-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033781578
179 https://doi.org/10.1007/s00251-003-0597-2
180 rdf:type schema:CreativeWork
181 sg:pub.10.1007/s00384-007-0396-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037191027
182 https://doi.org/10.1007/s00384-007-0396-6
183 rdf:type schema:CreativeWork
184 sg:pub.10.1038/nature03441 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050742226
185 https://doi.org/10.1038/nature03441
186 rdf:type schema:CreativeWork
187 sg:pub.10.1038/nbt1053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030939237
188 https://doi.org/10.1038/nbt1053
189 rdf:type schema:CreativeWork
190 sg:pub.10.1038/nrg3096 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011269644
191 https://doi.org/10.1038/nrg3096
192 rdf:type schema:CreativeWork
193 sg:pub.10.1038/onc.2015.399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017384962
194 https://doi.org/10.1038/onc.2015.399
195 rdf:type schema:CreativeWork
196 sg:pub.10.1038/sj.cdd.4401737 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001236310
197 https://doi.org/10.1038/sj.cdd.4401737
198 rdf:type schema:CreativeWork
199 sg:pub.10.1186/1471-2164-13-s1-s3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041782988
200 https://doi.org/10.1186/1471-2164-13-s1-s3
201 rdf:type schema:CreativeWork
202 sg:pub.10.1186/1471-2164-7-64 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012493227
203 https://doi.org/10.1186/1471-2164-7-64
204 rdf:type schema:CreativeWork
205 sg:pub.10.1186/1471-2407-8-264 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031823767
206 https://doi.org/10.1186/1471-2407-8-264
207 rdf:type schema:CreativeWork
208 sg:pub.10.1186/1475-4924-2-13 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029375403
209 https://doi.org/10.1186/1475-4924-2-13
210 rdf:type schema:CreativeWork
211 sg:pub.10.1186/gb-2004-5-10-r73 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043495139
212 https://doi.org/10.1186/gb-2004-5-10-r73
213 rdf:type schema:CreativeWork
214 sg:pub.10.1186/gb-2008-9-s1-s4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024435781
215 https://doi.org/10.1186/gb-2008-9-s1-s4
216 rdf:type schema:CreativeWork
217 sg:pub.10.1186/gb-2010-11-5-r53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012013843
218 https://doi.org/10.1186/gb-2010-11-5-r53
219 rdf:type schema:CreativeWork
220 sg:pub.10.1186/s12864-015-1511-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053563638
221 https://doi.org/10.1186/s12864-015-1511-7
222 rdf:type schema:CreativeWork
223 https://app.dimensions.ai/details/publication/pub.1074787296 schema:CreativeWork
224 https://app.dimensions.ai/details/publication/pub.1077478443 schema:CreativeWork
225 https://app.dimensions.ai/details/publication/pub.1082560041 schema:CreativeWork
226 https://app.dimensions.ai/details/publication/pub.1083068642 schema:CreativeWork
227 https://doi.org/10.1002/0471250953.bi0203s00 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026183986
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1002/0471250953.bi0807s7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000053539
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1002/j.1460-2075.1996.tb00706.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1082902155
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1006/jmbi.1999.2752 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001655546
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1016/0022-2836(82)90398-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025042064
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1016/j.aca.2008.07.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035973233
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1016/j.bbrc.2004.01.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051943115
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1016/j.bbrc.2008.03.136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041372035
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1016/j.bbrc.2014.06.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000937666
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1016/j.bbrc.2015.11.113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043510001
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1016/j.bioeng.2007.03.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009313636
248 rdf:type schema:CreativeWork
249 https://doi.org/10.1016/j.cell.2014.10.050 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013710164
250 rdf:type schema:CreativeWork
251 https://doi.org/10.1016/j.cellsig.2005.08.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051918495
252 rdf:type schema:CreativeWork
253 https://doi.org/10.1016/j.molimm.2011.05.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015786912
254 rdf:type schema:CreativeWork
255 https://doi.org/10.1016/s0076-6879(02)50979-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024630464
256 rdf:type schema:CreativeWork
257 https://doi.org/10.1042/bj20080476 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023394254
258 rdf:type schema:CreativeWork
259 https://doi.org/10.1074/jbc.272.47.29468 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026237241
260 rdf:type schema:CreativeWork
261 https://doi.org/10.1074/jbc.m112.447318 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015168851
262 rdf:type schema:CreativeWork
263 https://doi.org/10.1084/jem.181.4.1459 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049377611
264 rdf:type schema:CreativeWork
265 https://doi.org/10.1089/153623103322452378 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059215054
266 rdf:type schema:CreativeWork
267 https://doi.org/10.1093/bfgp/elp014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019553702
268 rdf:type schema:CreativeWork
269 https://doi.org/10.1093/bioinformatics/15.7.563 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030639875
270 rdf:type schema:CreativeWork
271 https://doi.org/10.1093/bioinformatics/btm462 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003107290
272 rdf:type schema:CreativeWork
273 https://doi.org/10.1093/nar/24.1.238 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031417336
274 rdf:type schema:CreativeWork
275 https://doi.org/10.1093/nar/gkh012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031148109
276 rdf:type schema:CreativeWork
277 https://doi.org/10.1093/nar/gki022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033237811
278 rdf:type schema:CreativeWork
279 https://doi.org/10.1093/nar/gki420 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016856957
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1093/nar/gkl995 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039365866
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1093/nar/gkm415 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003264848
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1093/nar/gkp335 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007915246
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1093/nar/gku1045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037369796
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1093/nar/gku1080 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035984294
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1093/nar/gkv1249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019852236
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1101/cshperspect.a001271 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044571076
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1101/gr.104216.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000604285
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1101/gr.225502 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045742587
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1101/gr.529803 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033963838
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1109/tcbb.2009.25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061540706
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1126/science.1090100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009574243
304 rdf:type schema:CreativeWork
305 https://doi.org/10.1126/science.8211139 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062653653
306 rdf:type schema:CreativeWork
307 https://doi.org/10.1128/mcb.10.4.1498 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025930926
308 rdf:type schema:CreativeWork
309 https://doi.org/10.1142/9789814447362_0014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1096039980
310 rdf:type schema:CreativeWork
311 https://doi.org/10.1142/s0219720006001849 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063004674
312 rdf:type schema:CreativeWork
313 https://doi.org/10.1210/mend.14.8.0506 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064332034
314 rdf:type schema:CreativeWork
315 https://doi.org/10.1242/jcs.02445 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034514170
316 rdf:type schema:CreativeWork
317 https://doi.org/10.1371/journal.pone.0046928 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035936855
318 rdf:type schema:CreativeWork
319 https://doi.org/10.1371/journal.pone.0057766 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018269824
320 rdf:type schema:CreativeWork
321 https://doi.org/10.3389/fphys.2013.00007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031299318
322 rdf:type schema:CreativeWork
323 https://doi.org/10.4049/jimmunol.178.11.7097 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030549107
324 rdf:type schema:CreativeWork
325 https://www.grid.ac/institutes/grid.208504.b schema:alternateName National Institute of Advanced Industrial Science and Technology
326 schema:name AIST, Artificial Intelligence Research Center, 2-4-7 Aomi, Koto-ku, 135-0064, Tokyo, Japan
327 rdf:type schema:Organization
328 https://www.grid.ac/institutes/grid.32197.3e schema:alternateName Tokyo Institute of Technology
329 schema:name Department of Computer Science, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, 152-8552, Tokyo, Japan
330 rdf:type schema:Organization
331 https://www.grid.ac/institutes/grid.452864.9 schema:alternateName Systems Biology Institute
332 schema:name Department of Ophthalmology and Visual Sciences, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City, 236-0004, Yokohama, Japan
333 Sony Computer Science Laboratories Inc., 3-14-13 Higashigotanda, Shinagawa-ku, 141-0022, Tokyo, Japan
334 Systems Biology Institute, 5-6-9 Shirokanedai, Minato-ku, 108-0071, Tokyo, Japan
335 rdf:type schema:Organization
336 https://www.grid.ac/institutes/grid.5801.c schema:alternateName Swiss Federal Institute of Technology in Zurich
337 schema:name Department of Biology, ETH Zurich, Wolfgang-Pauli-Strasse 27, 8093, Zurich, Switzerland
338 rdf:type schema:Organization
 




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


...