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IJON
2000
76views more  IJON 2000»
13 years 5 months ago
Fast neural network simulations with population density methods
The complexity of neural networks of the brain makes studying these networks through computer simulation challenging. Conventional methods, where one models thousands of individua...
Duane Q. Nykamp, Daniel Tranchina
CEC
2003
IEEE
13 years 11 months ago
Stochastic neural network models for gene regulatory networks
AbstractRecent advances in gene-expression profiling technologies provide large amounts of gene expression data. This raises the possibility for a functional understanding of geno...
Tianhai Tian, Kevin Burrage
BMCBI
2007
202views more  BMCBI 2007»
13 years 5 months ago
ProtNet: a tool for stochastic simulations of protein interaction networks dynamics
Background: Protein interactions support cell organization and mediate its response to any specific stimulus. Recent technological advances have produced large data-sets that aim ...
Massimo Bernaschi, Filippo Castiglione, Alessandra...
NN
2006
Springer
13 years 5 months ago
Propagation and control of stochastic signals through universal learning networks
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
Kotaro Hirasawa, Shingo Mabu, Jinglu Hu
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
13 years 12 months ago
Using pair approximations to predict takeover dynamics in spatially structured populations
The topological properties of a network directly impact the flow of information through a system. For example, in natural populations, the network of inter-individual contacts aff...
Joshua L. Payne, Margaret J. Eppstein