Sciweavers

30 search results - page 1 / 6
» Function approximation approach to the inference of reduced ...
Sort
View
BMCBI
2008
130views more  BMCBI 2008»
13 years 5 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...
BIRD
2008
Springer
141views Bioinformatics» more  BIRD 2008»
13 years 6 months ago
Nested q-Partial Graphs for Genetic Network Inference from "Small n, Large p" Microarray Data
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...
Kevin Kontos, Gianluca Bontempi
ICC
2007
IEEE
125views Communications» more  ICC 2007»
13 years 11 months ago
Scalable Fault Diagnosis in IP Networks using Graphical Models: A Variational Inference Approach
In this paper we investigate the fault diagnosis problem in IP networks. We provide a lower bound on the average number of probes per edge using variational inference technique pro...
Rajesh Narasimha, Souvik Dihidar, Chuanyi Ji, Stev...
EUSFLAT
2009
195views Fuzzy Logic» more  EUSFLAT 2009»
13 years 2 months ago
Optimization of an Oil Production System using Neural Networks and Genetic Algorithms
This paper proposes an optimization strategy which is based on neural networks and genetic algorithms to calculate the optimal values of gas injection rate and oil rate for oil pro...
Guillermo Jimenez de la Cruz, Jose A. Ruz-Hernande...
BMCBI
2007
197views more  BMCBI 2007»
13 years 5 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park