PLoS Computational Biology · 2011 · 14 citations · 29 references
Life SciencesBiologyCell BiologyCell SignalingNetwork BiologySignal TransductionBoolean Network ModelsCell Signaling NetworksInformation Flow In NetworksNetwork DynamicsSignal Transduction NetworksSignaling NetworksBiological SignalingBoolean EquationsBoolean Signaling NetworksCellular Information ProcessingSignal Network ModelingSignal Transduction Network ModelingSignal TransmissionSignaling Network Modeling
Living systems are capable of processing multiple sources of information simultaneously. This is true even at the cellular level, where not only coexisting signals stimulate the cell, but also the presence of fluctuating conditions is significant. When information is received by a cell signaling network via one specific input, the existence of other stimuli can provide a background activity -or chatter- that may affect signal transmission through the network and, therefore, the response of the cell. Here we study the modulation of information processing by chatter in the signaling network of a human cell, specifically, in a Boolean model of the signal transduction network of a fibroblast. We observe that the level of external chatter shapes the response of the system to information carrying signals in a nontrivial manner, modulates the activity levels of the network outputs, and effectively determines the paths of information flow. Our results show that the interactions and node dynamics, far from being random, confer versatility to the signaling network and allow transitions between different information-processing scenarios.
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