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DRAMATIC SIGNED

Development of Relevant Approaches to Mathematically Model Increasingly Complex Microbially-driven Processes

Total Cost €

0

EC-Contrib. €

0

Partnership

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Project "DRAMATIC" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITY OF NEWCASTLE UPON TYNE 

Organization address
address: KINGS GATE
city: NEWCASTLE UPON TYNE
postcode: NE1 7RU
website: http://www.ncl.ac.uk/

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website https://github.com/MI-SIM/DRAMATIC
 Total cost 255˙349 €
 EC max contribution 255˙349 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-GF
 Starting year 2017
 Duration (year-month-day) from 2017-06-01   to  2020-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITY OF NEWCASTLE UPON TYNE UK (NEWCASTLE UPON TYNE) coordinator 255˙349.00
2    MCMASTER UNIVERSITY CA (HAMILTON) partner 0.00

Map

 Project objective

Mathematical modelling has played a central role in understanding the fundamental characteristics and behaviour of ecological systems for over a century. In microbial systems, modelling has attempted to reveal the dynamics and interactions of simple co-cultures of organisms in chemostats through to more complex systems with highly diverse functionality. In real-world processes, such as engineered biological systems, EBS, (activated sludge, anaerobic digestion), the former models are incomplete for characterisation of the functional microbial diversity, whereas the latter models are intractable to mathematical analysis, rendering them as inadequate. The Fellowship will investigate the suitability of current mechanistic approaches to modelling for EBS using chemostat theory, but also exploring the analysis of higher dimensional models. The fellow will undertake their outgoing phase at McMaster University to develop their skills in dynamical system theory, applied to real-world systems and observed microbial ecological behaviour in various forms. This will include the use of both analytical and numerical methods to understand system stability and the detection of emergent properties. Recent advances in the understanding of the limits of classical Monod-type growth functions has given rise to new approaches including stochastic and diffusion-based models. However, mathematical investigation of these alternative concepts is not yet fully realised. The fellow will bridge the gap between microbial ecological theory, modelling and mathematical theory to understand the practical possibilities and predictive capabilities that can be exposed when rigorous analysis is achieved. As part of the return phase, he will spend a period at INRA, France, to investigate the validation and application of the models to real systems. This will be continued at Newcastle University, where dissemination of the outputs, including a dedicated software tool will be also be carried out.

 Publications

year authors and title journal last update
List of publications.
2019 Jing Chen, Matthew J. Wade, Jan Dolfing, Orkun S. Soyer
Increasing sulfate levels show a differential impact on synthetic communities comprising different methanogens and a sulfate reducer
published pages: 20190129, ISSN: 1742-5689, DOI: 10.1098/rsif.2019.0129
Journal of The Royal Society Interface 16/154 2019-08-30
2019 Wenfang Cai, Keaton Larson Lesnik, Matthew J. Wade, Elizabeth S. Heidrich, Yunhai Wang, Hong Liu
Incorporating microbial community data with machine learning techniques to predict feed substrates in microbial fuel cells
published pages: 64-71, ISSN: 0956-5663, DOI: 10.1016/j.bios.2019.03.021
Biosensors and Bioelectronics 133 2019-08-05
2018 Xin Zhang, Zizhen Zhang, Matthew J. Wade
Dynamical analysis of a competition and cooperation system with multiple delays
published pages: , ISSN: 1687-2770, DOI: 10.1186/s13661-018-1032-9
Boundary Value Problems 2018/1 2019-08-05

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