A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks

Open Access

Peer-reviewed

Research Article

Inés P. Mariño ,

* E-mail: ines.perez@urjc.es

Affiliations Departamento de Biología y Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, Móstoles, Madrid 28933, Spain, Institute for Women’s Health, University College London, London WC1E 6BT, United Kingdom

http://orcid.org/0000-0003-0152-0174

⨯
Alexey Zaikin,

Affiliations Institute for Women’s Health, University College London, London WC1E 6BT, United Kingdom, Department of Mathematics, University College London, London WC1E 6BT, United Kingdom, Department of Applied Mathematics, Lobachevsky State University of Nizhny Novgorod, Nizhniy Novgorod, Russia
⨯
Joaquín Míguez

Affiliation Departamento de Teoría de la Señal y Comunicaciones, Universidad Carlos III de Madrid, Leganés, Madrid, Spain
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Algorithms
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Monte Carlo method
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Markov models
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Covariance
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Computer modeling
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DNA transcription
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Probability density
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