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» Linear Modeling of Genetic Networks from Experimental Data
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AINA
2008
IEEE
14 years 1 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
CAV
2011
Springer
217views Hardware» more  CAV 2011»
12 years 11 months ago
From Cardiac Cells to Genetic Regulatory Networks
Abstract. A fundamental question in the treatment of cardiac disorders, such as tachycardia and fibrillation, is under what circumstances does such a disorder arise? To answer to ...
Radu Grosu, Grégory Batt, Flavio H. Fenton,...
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Accelerated search for biomolecular network models to interpret high-throughput experimental data
Background: The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein e...
Suman Datta, Bahrad A. Sokhansanj
IPSN
2004
Springer
14 years 22 days ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
BMCBI
2010
167views more  BMCBI 2010»
13 years 7 months ago
Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach
Background: Transcriptional gene regulation is one of the most important mechanisms in controlling many essential cellular processes, including cell development, cell-cycle contro...
Marc Bailly-Bechet, Alfredo Braunstein, Andrea Pag...