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JDCTA
2010
126views more  JDCTA 2010»
14 years 8 months ago
Continuous Neural Decoding Method Based on General Regression Neural Network
Neural decoding is an important task for understanding how the biological nervous system performs computation and communication. This paper introduces a novel continuous neural de...
Jianhua Dai, Xiaochun Liu, Shaomin Zhang, Huaijian...
PREMI
2007
Springer
15 years 8 months ago
Discovery of Process Models from Data and Domain Knowledge: A Rough-Granular Approach
The rapid expansion of the Internet has resulted not only in the ever-growing amount of data stored therein, but also in the burgeoning complexity of the concepts and phenomena per...
Andrzej Skowron
HYBRID
2001
Springer
15 years 6 months ago
Hybrid Modeling and Simulation of Biomolecular Networks
Abstract. In a biological cell, cellular functions and the genetic regulatory apparatus are implemented and controlled by a network of chemical reactions in which regulatory protei...
Rajeev Alur, Calin Belta, Franjo Ivancic
JBI
2002
15 years 1 months ago
Revising regulatory networks: from expression data to linear causal models
Discovering the complex regulatory networks that govern mRNA expression is an important but difficult problem. Many current approaches use only expression data from microarrays to...
Stephen D. Bay, Jeff Shrager, Andrew Pohorille, Pa...
INFORMATICALT
2008
120views more  INFORMATICALT 2008»
15 years 1 months ago
Nonlinear Behaviour in the MPI-Parallelised Model of the Rat Somatosensory Cortex
Mammalian brains consisting of up to 1011 neurons belong to group of the most complex systems in the Universe. For years they have been one of the hardest objects of simulation. Th...
Grzegorz M. Wojcik, Wieslaw A. Kaminski