Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

Implementing a multilayer framework for pathway data integration, analysis and visualization

Abstract: Personalized medicine, i.e. a medicine focused on the individual and proactive in nature, promises an improved health care by customizing the treatment according to patient needs. The methods to analyze data, model knowledge and store interpretable results vary widely. A common approach is to use networks for modelling and organizing this information. Network theory has been used for many years in the modelling and analysis of complex systems, as epidemiology, biology and biomedicine. As the data evolves and becomes more heterogeneous and complex, monoplex networks become an oversimplification of the corresponding systems. This imposes a need to go beyond traditional networks into a richer framework capable of hosting objects and relations of different scales, called Multilayered Network. These complex networks have contributed in many contexts and fields, and they are very applicable in the investigation of biological networks. In order to enrich this investigation, we aim to implement a multilayer framework that can be applicable in various domains, especially in the field of pathway modelling. Our idea is to integrate pathways and their related knowledge into a multilayer model, where each layer represents one of their elements. The model offers a feature we call “Selective Inclusion of Knowledge”, as well as a collection of related knowledge into a single graph, like diseases and drugs. The main layers are mapped to the entities of the pathways and the additional knowledge, for instance, a convenient model would have 3 layers respectively representing proteins, drugs and diseases. The model imports knowledge from multiple sources like the Reactome database, PharmGKB, DrugBank, OMIM and other public sources. The submitted poster will give an overview of the various models of multilayered networks, then it will describe the model we are building, and the workflow of implementing it into R as well as the future plan. The workflow consists of multiple R packages, of which we present the first implemented package, mully, that provides the multilayer layout. The data import and the integration will be done by another package to be implemented, Multipath.

Reliability assessment of integrated energy systems based on complex network theory

Abstract: As integrated energy systems (IES) continue to undergo development and advancement, the degree of coupling between subsystems and their complexity are also on the rise, posing a challenge for the reliability assessment of such systems. The conventional method is unable to explain the interaction between subsystems as well as system-level phenomena. The complex network theory is needed to provide a deeper analysis. Firstly, this paper introduces the basic concept and analysis tools of complex network theory. Secondly, the topological network model and the identification indexes of weak links for the IES are summarized as the basis for reliability assessment. Then, the reliability assessment indexes and assessment methods are sorted out for the IES based on the complex network theory; and further, the measures to optimize the reliability of the IES are put forward. Finally, from the perspective of complex network theory, directions for future research on the reliability assessment of IES are suggested.

Network theory meets history. Local balance in global international relations

Abstract: The resulting effect of global international relations is an intricate and dynamic web of alliances and conflicts. Here, we represent this web as a time-evolving signed network and define an index quantifying the proximity of every nation to its balanced condition. This condition emerges when a given nation belongs to a bloc of allies that only have enmities with a different confronted bloc. However, we find that large blocs of allies percolated by a tiny clique of mutual enemies, which are ubiquitous across history, are very unstable in terms of their balanced condition. We design a quantitative history approach to identify the nations playing a fundamental role in major events in human history over a period of almost 200 years. It is combined with historic narrative and the sociopolitical theory of balance of power to build up a new mixed approach to history based on network theory.

he application of network theory in official statistics

Abstract: The challenges faced by official statistics in the 21st century are manifold. We are surrounded by systems that are becoming substantially more complex. The emergence of new phenomena, such as globalisation, digitalisation, has increased the complexity of the reality that needs to be meaningfully and timeously captured by official statistics; it has resulted in the development of new patterns, routes, and types of data, giving us the opportunity to further improve the relevance of statistics. In response to these trends, we need to find new tools and methods for the measurement of these dynamic phenomena. Network theory is an innovative approach that can help us handle the complexity of the 21st century. However, so far it has not featured in mainstream official statistics.