Managing models of signaling networks

Neurocomputing

Volumn 52-54, Issue , 2003, Pages 215-220

  Bhalla, Upinder S ^a  

^a TATA INSTITUTE OF FUNDAMENTAL RESEARCH   (India)

Author keywords

Database; Mass action chemistry; Signaling pathways; Simulation

Indexed keywords

CELLS; COMPUTATIONAL METHODS; PLASTICITY; REACTION KINETICS; SIGNALING;

SYNAPTIC PLASTICITY;

NEUROLOGY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CELL COMMUNICATION; CELL FUNCTION; CHEMICAL INTERACTION; CONTROLLED STUDY; DATA BASE; INFORMATION PROCESSING; KINETICS; MASS ACTION; NERVE CELL PLASTICITY; PRIORITY JOURNAL; SIGNAL TRANSDUCTION;

EID: 0038458814     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(02)00737-3     Document Type: Article

References (8)

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2. U.S. Bhalla, The chemical organization of signaling interactions, Bioinformatics 18 (2002) 855-863.
3. U.S. Bhalla, R. Iyengar, Emergent properties of networks of biological signaling pathways, Science 283 (1999) 381-387.
4. T.V.P. Bliss, G.L. Collingridge, A synaptic model of memory: long-term potentiation in the hippocampus, Nature 361 (1993) 31-39.
5. D. Bray, Protein molecules as computational elements in living cells, Nature 376 (1995) 307-312.
6. S. Sivakumaran, S. Hariharaputran, J. Mishra, U.S. Bhalla, The database of Quantitative Cellular Signaling: management and analysis of chemical kinetic models of signaling networks, Bioinformatics, in press.
7. J.R. Stiles, T.M. Bartol, Monte Carlo methods for simulating realistic synaptic microphysiology using MCell, in: E. De Schutter (Ed.), Computational Neuroscience: Realistic Modeling for Experimentalists, CRC Press, Boca Raton, 2000, pp. 87-128.
8. G. Weng, U.S. Bhalla, R. Iyengar, Complexity in biological signaling systems, Science 284 (1999) 92-96.