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.
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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 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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