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BMCBI
2007
173views more  BMCBI 2007»
13 years 8 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...
BIOCOMP
2010
13 years 6 months ago
A Model Reduction Technique for Stochastic Biochemical Kinetics
Abstract-- Modeling the intermolecular reactions in a single cell is a critical problem in computational biology. Biochemical reaction systems often involve species in both low and...
Silvana Ilie, Ekaterina Kudashkina
CEC
2007
IEEE
14 years 2 months ago
Evolving neuromodulatory topologies for reinforcement learning-like problems
— Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advanta...
Andrea Soltoggio, Peter Dürr, Claudio Mattius...
BC
2000
95views more  BC 2000»
13 years 8 months ago
Cerebellar learning of accurate predictive control for fast-reaching movements
Long conduction delays in the nervous system prevent the accurate control of movements by feedback control alone. We present a new, biologically plausible cerebellar model to study...
Jacob Spoelstra, Nicolas Schweighofer, Michael A. ...
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
14 years 4 days ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing