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DYNASNET SIGNED

Dynamics and Structure of Networks

Total Cost €

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EC-Contrib. €

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Partnership

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Project "DYNASNET" data sheet

The following table provides information about the project.

Coordinator
MAGYAR TUDOMANYOS AKADEMIA RENYI ALFRED MATEMATIKAI KUTATOINTEZET 

Organization address
address: REALTANODA UTCA 13-15
city: Budapest
postcode: 1053
website: http://www.renyi.hu

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 Hungary [HU]
 Total cost 9˙315˙424 €
 EC max contribution 9˙315˙424 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-SyG
 Funding Scheme ERC-SyG
 Starting year 2019
 Duration (year-month-day) from 2019-09-01   to  2025-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    MAGYAR TUDOMANYOS AKADEMIA RENYI ALFRED MATEMATIKAI KUTATOINTEZET HU (Budapest) coordinator 3˙484˙324.00
2    KOZEP-EUROPAI EGYETEM HU (BUDAPEST) participant 3˙799˙850.00
3    UNIVERZITA KARLOVA CZ (PRAHA 1) participant 2˙031˙250.00

Map

 Project objective

Networks define our life, being essential to cell biology, communications, social and economic systems, and impacting virtually all areas of science and technology. The aim of this proposal is to engage leading experts in network science and graph theory to build a mathematically sound theory of dynamical networks, which will be transformative to our understanding of complex systems, with applications in multiple disciplines. Both fields have made major conceptual advances in the past decade: network science has offered a data-based basic topological description of complex networks, and has started to address the inherently dynamical nature of real networks, their reconstruction and control; in mathematics we have seen major advances in graph limit theory, the local-global dichotomy in observation, and promising steps in the theory of graphs with intermediate degrees, that capture real networks. While these concepts offer different formalisms to capture the same underlying reality, there has been no conversation between the two communities, limiting our understanding of real networks. The proposed research aims to build on these advances to construct a coherent theory of dynamical networks, and to exploit its applications and predictive power to various real systems. We plan to offer a sound mathematical foundation of network science, helping us better analyze, predict and control the behavior of real networks. It will benefit mathematics in leading to an enriched, robust graph limit theory, with exciting applications in multiple areas of mathematics. To enhance the wider impact of the proposed mathematical advances, we plan to conduct a permanent conversation with experts from different domains that encounter and explore real networks, from cell biology to brain science and transportation and communication networks, inspiring with novel questions and helping the application of our advances in these domains.

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The information about "DYNASNET" are provided by the European Opendata Portal: CORDIS opendata.

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