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@ARTICLE{Iyappan:138638,
      author       = {Iyappan, Anandhi and Gündel, Michaela and Shahid, Mohammad
                      and Wang, Jiali and Li, Hui and Mevissen, Heinz-Theodor and
                      Müller, Bernd and Fluck, Juliane and Jirsa, Viktor and
                      Domide, Lia and Younesi, Erfan and Hofmann-Apitius, Martin},
      title        = {{T}owards a {P}athway {I}nventory of the {H}uman {B}rain
                      for {M}odeling {D}isease {M}echanisms {U}nderlying
                      {N}eurodegeneration.},
      journal      = {Journal of Alzheimer's disease},
      volume       = {52},
      number       = {4},
      issn         = {1387-2877},
      address      = {Amsterdam},
      publisher    = {IOS Press},
      reportid     = {DZNE-2020-04960},
      pages        = {1343-1360},
      year         = {2016},
      abstract     = {Molecular signaling pathways have been long used to
                      demonstrate interactions among upstream causal molecules and
                      downstream biological effects. They show the signal flow
                      between cell compartments, the majority of which are
                      represented as cartoons. These are often drawn manually by
                      scanning through the literature, which is time-consuming,
                      static, and non-interoperable. Moreover, these pathways are
                      often devoid of context (condition and tissue) and biased
                      toward certain disease conditions. Mining the scientific
                      literature creates new possibilities to retrieve pathway
                      information at higher contextual resolution and specificity.
                      To address this challenge, we have created a pathway
                      terminology system by combining signaling pathways and
                      biological events to ensure a broad coverage of the entire
                      pathway knowledge domain. This terminology was applied to
                      mining biomedical papers and patents about neurodegenerative
                      diseases with focus on Alzheimer's disease. We demonstrate
                      the power of our approach by mapping literature-derived
                      signaling pathways onto their corresponding anatomical
                      regions in the human brain under healthy and Alzheimer's
                      disease states. We demonstrate how this knowledge resource
                      can be used to identify a putative mechanism explaining the
                      mode-of-action of the approved drug Rasagiline, and show how
                      this resource can be used for fingerprinting patents to
                      support the discovery of pathway knowledge for Alzheimer's
                      disease. Finally, we propose that based on next-generation
                      cause-and-effect pathway models, a dedicated inventory of
                      computer-processable pathway models specific to
                      neurodegenerative diseases can be established, which
                      hopefully accelerates context-specific enrichment analysis
                      of experimental data with higher resolution and richer
                      annotations.},
      keywords     = {Brain: drug effects / Brain: metabolism / Brain:
                      physiopathology / Databases, Factual / Humans / Metabolic
                      Networks and Pathways: physiology / Models, Neurological /
                      Neurodegenerative Diseases: metabolism / Neurodegenerative
                      Diseases: physiopathology / Signal Transduction: physiology
                      / Terminology as Topic},
      cin          = {AG Breteler},
      ddc          = {610},
      cid          = {I:(DE-2719)1012001},
      pnm          = {345 - Population Studies and Genetics (POF3-345)},
      pid          = {G:(DE-HGF)POF3-345},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:27079715},
      doi          = {10.3233/JAD-151178},
      url          = {https://pub.dzne.de/record/138638},
}