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000138638 041__ $$aEnglish
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000138638 1001_ $$0P:(DE-HGF)0$$aIyappan, Anandhi$$b0
000138638 245__ $$aTowards a Pathway Inventory of the Human Brain for Modeling Disease Mechanisms Underlying Neurodegeneration.
000138638 260__ $$aAmsterdam$$bIOS Press$$c2016
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000138638 520__ $$aMolecular signaling pathways have been long used to demonstrate interactions among upstream causal molecules and downstream biological effects. They show the signal flow between cell compartments, the majority of which are represented as cartoons. These are often drawn manually by scanning through the literature, which is time-consuming, static, and non-interoperable. Moreover, these pathways are often devoid of context (condition and tissue) and biased toward certain disease conditions. Mining the scientific literature creates new possibilities to retrieve pathway information at higher contextual resolution and specificity. To address this challenge, we have created a pathway terminology system by combining signaling pathways and biological events to ensure a broad coverage of the entire pathway knowledge domain. This terminology was applied to mining biomedical papers and patents about neurodegenerative diseases with focus on Alzheimer's disease. We demonstrate the power of our approach by mapping literature-derived signaling pathways onto their corresponding anatomical regions in the human brain under healthy and Alzheimer's disease states. We demonstrate how this knowledge resource can be used to identify a putative mechanism explaining the mode-of-action of the approved drug Rasagiline, and show how this resource can be used for fingerprinting patents to support the discovery of pathway knowledge for Alzheimer's disease. Finally, we propose that based on next-generation cause-and-effect pathway models, a dedicated inventory of computer-processable pathway models specific to neurodegenerative diseases can be established, which hopefully accelerates context-specific enrichment analysis of experimental data with higher resolution and richer annotations.
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000138638 650_2 $$2MeSH$$aBrain: drug effects
000138638 650_2 $$2MeSH$$aBrain: metabolism
000138638 650_2 $$2MeSH$$aBrain: physiopathology
000138638 650_2 $$2MeSH$$aDatabases, Factual
000138638 650_2 $$2MeSH$$aHumans
000138638 650_2 $$2MeSH$$aMetabolic Networks and Pathways: physiology
000138638 650_2 $$2MeSH$$aModels, Neurological
000138638 650_2 $$2MeSH$$aNeurodegenerative Diseases: metabolism
000138638 650_2 $$2MeSH$$aNeurodegenerative Diseases: physiopathology
000138638 650_2 $$2MeSH$$aSignal Transduction: physiology
000138638 650_2 $$2MeSH$$aTerminology as Topic
000138638 7001_ $$0P:(DE-HGF)0$$aGündel, Michaela$$b1
000138638 7001_ $$0P:(DE-2719)2811036$$aShahid, Mohammad$$b2$$udzne
000138638 7001_ $$0P:(DE-HGF)0$$aWang, Jiali$$b3
000138638 7001_ $$0P:(DE-HGF)0$$aLi, Hui$$b4
000138638 7001_ $$0P:(DE-HGF)0$$aMevissen, Heinz-Theodor$$b5
000138638 7001_ $$0P:(DE-HGF)0$$aMüller, Bernd$$b6
000138638 7001_ $$0P:(DE-HGF)0$$aFluck, Juliane$$b7
000138638 7001_ $$0P:(DE-HGF)0$$aJirsa, Viktor$$b8
000138638 7001_ $$0P:(DE-HGF)0$$aDomide, Lia$$b9
000138638 7001_ $$0P:(DE-HGF)0$$aYounesi, Erfan$$b10
000138638 7001_ $$0P:(DE-HGF)0$$aHofmann-Apitius, Martin$$b11
000138638 77318 $$2Crossref$$3journal-article$$a10.3233/jad-151178$$b : IOS Press, 2016-06-07$$n4$$p1343-1360$$tJournal of Alzheimer's Disease$$v52$$x1387-2877$$y2016
000138638 773__ $$0PERI:(DE-600)2070772-1$$a10.3233/JAD-151178$$gVol. 52, no. 4, p. 347 - 355$$n4$$p1343-1360$$q52:4<347 - 355$$tJournal of Alzheimer's disease$$v52$$x1387-2877$$y2016
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