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Bayesian inference for duplication-mutation with complementarity network models

Jasra, A; Persing, A; Beskos, A; Heine, K; De Iorio, M; (2015) Bayesian inference for duplication-mutation with complementarity network models. Journal of Computational Biology , 22 (11) pp. 1025-1033. 10.1089/cmb.2015.0072. Green open access

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Abstract

We observe an undirected graph G without multiple edges and self-loops, which is to represent a protein-protein interaction (PPI) network. We assume that G evolved under the duplication-mutation with complementarity (DMC) model from a seed graph, G0, and we also observe the binary forest Γ that represents the duplication history of G. A posterior density for the DMC model parameters is established, and we outline a sampling strategy by which one can perform Bayesian inference; that sampling strategy employs a particle marginal Metropolis-Hastings (PMMH) algorithm. We test our methodology on numerical examples to demonstrate a high accuracy and precision in the inference of the DMC model's mutation and homodimerization parameters.

Type: Article
Title: Bayesian inference for duplication-mutation with complementarity network models
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1089/cmb.2015.0072
Publisher version: http://dx.oi.org/10.1089/cmb.2015.0072
Additional information: © The Authors 2015; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
Keywords: duplication–mutation with complementarity (DMC) model, particle marginal Metropolis–Hastings (PMMH), protein–protein interaction (PPI) network, sequential Monte Carlo (SMC)
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/1465703
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