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» Using Bayesian networks to analyze expression data
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TNN
1998
111views more  TNN 1998»
15 years 3 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
142
Voted
VIZSEC
2005
Springer
15 years 9 months ago
IDGraphs: Intrusion Detection and Analysis Using Histographs
Traffic anomalies and attacks are commonplace in today’s networks and identifying them rapidly and accurately is critical for large network operators. For a statistical intrusi...
Pin Ren, Yan Gao, Zhichun Li, Yan Chen, Benjamin W...
EMO
2005
Springer
108views Optimization» more  EMO 2005»
15 years 9 months ago
Multi-objective Model Optimization for Inferring Gene Regulatory Networks
With the invention of microarray technology, researchers are able to measure the expression levels of ten thousands of genes in parallel at various time points of a biological proc...
Christian Spieth, Felix Streichert, Nora Speer, An...
124
Voted
CMSB
2009
Springer
15 years 10 months ago
Modelling Biological Clocks with Bio-PEPA: Stochasticity and Robustness for the Neurospora crassa Circadian Network
Circadian clocks are biochemical networks, present in nearly all living organisms, whose function is to regulate the expression of specific mRNAs and proteins to synchronise rhyth...
Ozgur E. Akman, Federica Ciocchetta, Andrea Degasp...
RAID
2004
Springer
15 years 9 months ago
HoneyStat: Local Worm Detection Using Honeypots
Worm detection systems have traditionally used global strategies and focused on scan rates. The noise associated with this approach requires statistical techniques and large data s...
David Dagon, Xinzhou Qin, Guofei Gu, Wenke Lee, Ju...