Abbas K. Rizi

Abbas K. Rizi
Aalto University · Department of Computer Science

PhD Candidate
Playing with Networks!

About

14
Publications
798
Reads
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22
Citations

Publications

Publications (14)
Article
Full-text available
We study how the herd immunity threshold and the expected epidemic size depend on homophily with respect to vaccine adoption. We find that the presence of homophily considerably increases the critical vaccine coverage needed for herd immunity and that strong homophily can push the threshold entirely out of reach. The epidemic size monotonically inc...
Article
Full-text available
Contact tracing via digital tracking applications installed on mobile phones is an important tool for controlling epidemic spreading. Its effectivity can be quantified by modifying the standard methodology for analyzing percolation and connectivity of contact networks. We apply this framework to networks with varying degree distributions, numbers o...
Preprint
Full-text available
Even partial immunity may prevent infectious diseases from spreading at the population level, bringing the system below the epidemic threshold. This effect is known as herd immunity. We study how the vaccination threshold for herd immunity and the expected epidemic size depend on homophily in vaccine adoption. We find that already a small level of...
Preprint
Full-text available
The event graph representation of temporal networks suggests that the connectivity of temporal structures can be mapped to a directed percolation problem. However, similar to percolation theory on static networks, this mapping is valid under the approximation that the structure and interaction dynamics of the temporal network are determined by its...
Article
Full-text available
In this study, we investigated cancer cellular networks in the context of gene interactions and their associated patterns in order to recognize the structural features underlying this disease. We aim to propose that the quest of understanding cancer takes us beyond pairwise interactions between genes to a higher-order construction. We characterize...
Preprint
Full-text available
Connectivity transitions in static networks are well described by percolation theory, yet the corresponding description is not developed for temporal networks. We map the connectivity problem of temporal networks to directed percolation and show that the reachability phase transition in random temporal network models, as induced by any limited-wait...
Preprint
Full-text available
Contact tracing via digital tracking applications installed on mobile phones is an important tool for controlling epidemic spreading. Its effectivity can be quantified by modifying the standard methodology for analyzing percolation and connectivity of contact networks. We apply this framework for networks with varying degree distribution, the numbe...
Preprint
Full-text available
In this study, we investigated cancer cellular networks in the context of gene interactions and their associated patterns in order to recognize the structural features underlying this disease. We aim to propose that the quest of understanding cancer takes us beyond pairwise interactions between genes to a higher-order construction. We characterize...
Article
Full-text available
Genes communicate with each other through different regulatory effects, which lead to the emergence of complex network structures in cells, and such structures are expected to be different for normal and cancerous cells. To study these differences, we have investigated the Gene Regulatory Network (GRN) of cells as inferred from RNA-sequencing data....
Preprint
Full-text available
Genes communicate with each other through different regulatory effects, which lead to the emergence of complex structures in cells, and such structures are expected to be different for normal and cancerous cells. To study breast cancer differences, we have investigated the Gene Regulatory Network (GRN) of cells as inferred from RNA-sequencing data....
Preprint
Full-text available
We present a fractional model to clarify the dynamical evolution of how and under what circumstances--in a multi-agent economic area--newly founded ventures prolong their existence throughout the market. Since the increase in the number of newly-established firms in a market may generally lead to the reduction of the market share of players in the...

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Projects

Projects (2)
Project
Cancer is commonly known as a disease of the genes. Almost all the studies about cancer are based on finding effective genes for each type of cancer and neglecting the collective behavior of the genes emerged from the regulatory effects of them on each other in a cell. In our study, we have considered each gene as a spin in a spin-glass (multivariate Gaussian) model and the gene-gene interaction as the coupling between each pair of the spins. By applying the principle of max. entropy, we have inferred the network of interactions from RNA-Seq data of genes expression levels in the case of Breast Cancer. This network is a signed weighted network, so according to the framework of Balance Theory, we could assign energy to the triads and the entire network.
Project
In studying the network dynamics of complex systems such as the world-wide web, genes regulatory networks, and social networks it regularly happens that we do not have access to the complete information about them. Not only the information is incomplete, but also some of the information may be wrong. So, how can we understand the general or particular behavior of such networks in these scenarios?! In this type of giant networks, a new and very interesting type of uncertainty arises when there is absolutely no guarantee whether a node or a link is visible at all for some parties. There is a network of colleagues, a network of high school classmates, a network of friends in Facebook, a network of relatives and so many other networks forming a very big puzzle of different types of relationships. This puzzle is like a multilayer or multidimensional network which we call it, the Dark Network, a network of networks, containing the whole information of socio-technical or biological systems. Almost no one can have access to the Dark Network, and even if some does, it is a not a kind of problems to be solved computationally! What supercomputer can handle this amount of data? This problem can even get more interesting when the present knowledge between the parties are not the same! What type of effort can we make to settle the dispute between two agents or parties when they have different pictures of something in common? Notice that every two contradicting perspectives about such situations can be correct, depending on what side you are looking at the problem! We are actually developing physics-based algorithms which can point to hidden connections between spatially disparate nodes of the Dark Network. This includes finding clusters and communities emerged from such a many-many-body system, especially when the expectation of sub-networks about the whole picture are contradicting each other.