A novel approach to model neuronal signal transduction using stochastic differential equations

Neurocomputing

Volumn 69, Issue 10-12, 2006, Pages 1066-1069

  Manninen, Tiina ^a   Linne, Marja Leena ^a   Ruohonen, Keijo ^a  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

Euler Maruyama method; It form; Protein kinase C; Signal transduction; Stochastic differential equation

Indexed keywords

COMPUTER SIMULATION; DIFFERENTIAL EQUATIONS; INTEGRATION; MATHEMATICAL MODELS; NUMERICAL METHODS; PROTEINS; RANDOM PROCESSES;

EULER-MARUYAMA METHOD; NEURONAL SIGNAL TRANSDUCTION; PROTEIN KINASE C; STOCHASTIC DIFFERENTIAL EQUATIONS;

NEURAL NETWORKS;

PROTEIN KINASE C;

ARTICLE; AUTOMATION; CHEMICAL INTERACTION; COMPUTER SIMULATION; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; NERVE CELL NETWORK; NERVE CELL STIMULATION; NEUROTRANSMISSION; PRIORITY JOURNAL; RELIABILITY; SIGNAL TRANSDUCTION; STOCHASTIC MODEL;

EID: 33646104196     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2005.12.047     Document Type: Article

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