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» Least-squares methods for identifying biochemical regulatory...
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BMCBI
2007
63views more  BMCBI 2007»
13 years 11 months ago
Least-squares methods for identifying biochemical regulatory networks from noisy measurements
Jongrae Kim, Declan G. Bates, Ian Postlethwaite, P...
CEC
2010
IEEE
13 years 5 months ago
Parameter estimation with term-wise decomposition in biochemical network GMA models by hybrid regularized Least Squares-Particle
High-throughput analytical techniques such as nuclear magnetic resonance, protein kinase phosphorylation, and mass spectroscopic methods generate time dense profiles of metabolites...
Prospero C. Naval, Luis G. Sison, Eduardo R. Mendo...
ICASSP
2010
IEEE
13 years 11 months ago
A convex relaxation for approximate maximum-likelihood 2D source localization from range measurements
This paper addresses the problem of locating a single source from noisy range measurements in wireless sensor networks. An approximate solution to the maximum likelihood location ...
Pinar Oguz-Ekim, João Pedro Gomes, Jo&atild...
BMCBI
2010
172views more  BMCBI 2010»
13 years 11 months ago
Comparison of evolutionary algorithms in gene regulatory network model inference
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Alina Sîrbu, Heather J. Ruskin, Martin Crane
BMCBI
2006
127views more  BMCBI 2006»
13 years 11 months ago
On the attenuation and amplification of molecular noise in genetic regulatory networks
Background: Noise has many important roles in cellular genetic regulatory functions at the nanomolar scale. At present, no good theory exists for identifying all possible mechanis...
Bor-Sen Chen, Yu-Chao Wang