Conference Proceedings
IMPARO: Inferring microbial interactions through parameter optimisation
R Vidanaarachchi, M Shaw, SL Tang, S Halgamuge
BMC Molecular and Cell Biology | BMC | Published : 2020
Abstract
Background: Microbial Interaction Networks (MINs) provide important information for understanding bacterial communities. MINs can be inferred by examining microbial abundance profiles. Abundance profiles are often interpreted with the Lotka Volterra model in research. However existing research fails to consider a biologically meaningful underlying mathematical model for MINs or to address the possibility of multiple solutions. Results: In this paper we present IMPARO, a method for inferring microbial interactions through parameter optimisation. We use biologically meaningful models for both the abundance profile, as well as the MIN. We show how multiple MINs could be inferred with similar re..
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Awarded by Australian Research Council
Funding Acknowledgements
Publication of this supplement was funded by the Australia Research Council [grant number DP150103512]. RV was funded by scholarships of The Australian National University. Resources and facilities at The Australian National University, The University of Melbourne and Academia Sinica were used for this research.