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Discovering dominant pathways and signal-response relationships in signaling networks through nonparametric approaches

Nassiri, I ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1016/j.ygeno.2013.07.012
  3. Publisher: 2013
  4. Abstract:
  5. A signaling pathway is a sequence of proteins and passenger molecules that transmits information from the cell surface to target molecules. Understanding signal transduction process requires detailed description of the involved pathways. Several methods and tools resolved this problem by incorporating genomic and proteomic data. However, the difficulty of obtaining prior knowledge of complex signaling networks limited the applicability of these tools. In this study, based on the simulation of signal flow in signaling network, we introduce a method for determining dominant pathways and signal response to stimulations. The model uses topology-weighted transit compartment approach and comprises four main steps which include weighting the edges, simulating signal transduction in the network (weighting the nodes), finding paths between initial and target nodes, and assigning a significance score to each path. We applied the proposed model to eighty-three signaling networks by using biologically derived source and sink molecules. The recovered dominant paths matched many known signaling pathways and suggesting a promising index to analyze the phenotype essentiality of molecule encoding paths. We also modeled the stimulus-response relations in long and short-term synaptic plasticity based on the dominant signaling pathway concept. We showed that the proposed method not only accurately determines dominant signaling pathways, but also identifies effective points of intervention in signal transduction
  6. Keywords:
  7. Dose-response relationship ; Molecular targeted therapy ; Neuronal plasticity ; Calculation ; Controlled study ; Evolutionary rate ; Hippocampal CA1 region ; Long term depression ; Long term potentiation ; Mathematical computing ; Mathematical model ; Molecular model ; Nerve cell plasticity ; Phenotypic variation ; Priority journal ; Scoring system ; Signal transduction ; Simulation ; Stimulus response ; Validation process ; Signaling pathway ; Algorithms ; Animals ; Computer simulation ; Data mining ; Databases, protein ; Humans ; Models, biological ; Models, statistical ; Phenotype ; Protein interaction maps ; Proteins ; Proteomics ; Secondary metabolism ; Statistics, nonparametric
  8. Source: Genomics ; Volume 102, Issue 4 , October , 2013 , Pages 195-201 ; 08887543 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0888754313001493