Gene regulatory network state estimation from arbitrary correlated measurements

Gene regulatory network state estimation from arbitrary correlated measurements

Abstract Background Advancements in gene expression technology allow acquiring cheap and abundant data for analyzing cell behavior. However, these technologies produce noisy, and often correlated, measurements on the transcriptional states of genes. The Boolean network model has been shown to be eff...

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Bibliographic Details
Main Authors: Mahdi Imani, Ulisses Braga-Neto
Format: Article
Language:English
Published: SpringerOpen 2018-04-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
State estimation
Partially-observed Boolean dynamical system
Correlated measurement noise
Gene regulatory network
Boolean Kalman Filter and Smoother
Online Access:http://link.springer.com/article/10.1186/s13634-018-0543-y

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http://link.springer.com/article/10.1186/s13634-018-0543-y

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