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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2010
98views more  BMCBI 2010»
13 years 7 months ago
A semi-nonparametric mixture model for selecting functionally consistent proteins
Background: High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experim...
Lianbo Yu, R. W. Doerge
BMCBI
2008
89views more  BMCBI 2008»
13 years 7 months ago
Increasing the efficiency of bacterial transcription simulations: When to exclude the genome without loss of accuracy
Background: Simulating the major molecular events inside an Escherichia coli cell can lead to a very large number of reactions that compose its overall behaviour. Not only should ...
Marco A. J. Iafolla, Guang Qiang Dong, David R. Mc...
BMCBI
2006
130views more  BMCBI 2006»
13 years 7 months ago
An accurate and interpretable model for siRNA efficacy prediction
Background: The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional s...
Jean-Philippe Vert, Nicolas Foveau, Christian Laja...
TNN
1998
111views more  TNN 1998»
13 years 7 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos
EUROGP
2007
Springer
104views Optimization» more  EUROGP 2007»
14 years 1 months ago
Code Regulation in Open Ended Evolution
We explore a homeostatic approach to program execution in computer systems: the “concentration” of computation services is regulated according to their fitness. The goal is to...
Lidia Yamamoto