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@ARTICLE{Porras:137882,
      author       = {Porras, Pablo and Duesbury, Margaret and Fabregat, Antonio
                      and Ueffing, Marius and Orchard, Sandra and Gloeckner,
                      Christian Johannes and Hermjakob, Henning},
      title        = {{A} visual review of the interactome of {LRRK}2: {U}sing
                      deep-curated molecular interaction data to represent
                      biology.},
      journal      = {Practical proteomics},
      volume       = {15},
      number       = {8},
      issn         = {1615-9853},
      address      = {Weinheim},
      publisher    = {Wiley VCH69157},
      reportid     = {DZNE-2020-04204},
      pages        = {1390-1404},
      year         = {2015},
      abstract     = {Molecular interaction databases are essential resources
                      that enable access to a wealth of information on
                      associations between proteins and other biomolecules.
                      Network graphs generated from these data provide an
                      understanding of the relationships between different
                      proteins in the cell, and network analysis has become a
                      widespread tool supporting -omics analysis. Meaningfully
                      representing this information remains far from trivial and
                      different databases strive to provide users with detailed
                      records capturing the experimental details behind each piece
                      of interaction evidence. A targeted curation approach is
                      necessary to transfer published data generated by primarily
                      low-throughput techniques into interaction databases. In
                      this review we present an example highlighting the value of
                      both targeted curation and the subsequent effective
                      visualization of detailed features of manually curated
                      interaction information. We have curated interactions
                      involving LRRK2, a protein of largely unknown function
                      linked to familial forms of Parkinson's disease, and hosted
                      the data in the IntAct database. This LRRK2-specific dataset
                      was then used to produce different visualization examples
                      highlighting different aspects of the data: the level of
                      confidence in the interaction based on orthogonal evidence,
                      those interactions found under close-to-native conditions,
                      and the enzyme-substrate relationships in different in vitro
                      enzymatic assays. Finally, pathway annotation taken from the
                      Reactome database was overlaid on top of interaction
                      networks to bring biological functional context to
                      interaction maps.},
      subtyp        = {Review Article},
      keywords     = {Animals / Computer Graphics / Databases, Protein / Humans /
                      Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 /
                      Molecular Sequence Annotation / Parkinson Disease:
                      metabolism / Protein Interaction Maps /
                      Protein-Serine-Threonine Kinases: physiology / Proteomics:
                      methods / Software / LRRK2 protein, human (NLM Chemicals) /
                      Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 (NLM
                      Chemicals) / Protein-Serine-Threonine Kinases (NLM
                      Chemicals)},
      cin          = {AG Gloeckner},
      ddc          = {540},
      cid          = {I:(DE-2719)1210007},
      pnm          = {345 - Population Studies and Genetics (POF3-345)},
      pid          = {G:(DE-HGF)POF3-345},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:25648416},
      pmc          = {pmc:PMC4415485},
      doi          = {10.1002/pmic.201400390},
      url          = {https://pub.dzne.de/record/137882},
}