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Title:
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Sensitivity and Specificity of Inferring Genetic Regulatory Interactions with the VBEM Algorithm |
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Author(s):
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Isabel M. Tienda-luna , Maria C. Carrion Perez , Diego P. Ruiz Padillo , Yufang Yin , Yufei Huang |
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ISBN:
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ISSN: 1646-3692 |
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Editors:
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Mohammad Essaaidi and Mohammed El Mohajir (Guest Editors) |
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Year:
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2009 |
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Edition:
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V IV, 1 |
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Keywords:
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Gene networks, Microarray data, Bayesian inference, Variational Bayesian Expectation
Maximization, ROC curves |
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Type:
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Journal Paper |
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First Page:
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54 |
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Last Page:
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63 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In this paper we perform a study of the performance of the VBEM algorithm proposed in [19]. The
VBEM is a Bayesian approach for reconstructing gene regulatory networks (GRNs) based on microarray
data. We focus on a variable selection formulation and develop a solution by a variational Bayes Expectation
Maximization (VBEM) learning rule. The major advantage of the VBEM solution over Monte Carlo
sampling based approach is its lower computational complexity. This makes it appealing for uncovering
large networks. The suitability of the proposed algorithm to infer large networks is studied in terms of
its ROC curves. |
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