| 1. |
- Holme, Petter, 1973-, et al.
(författare)
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Multiscaling in an YX model of networks
- 2009
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Ingår i: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics. - 1063-651X .- 1095-3787. ; 80, s. 036120-
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Tidskriftsartikel (refereegranskat)abstract
- Weinvestigate a Hamiltonian model of networks. The model is amirror formulation of the XY model (hence the name)—instead ofletting the XY spins vary, keeping the coupling topology static,we keep the spins conserved and sample different underlying networks.Our numerical simulations show complex scaling behaviors with various exponentsas the system grows and temperature approaches zero, but nofinite-temperature universal critical behavior. The ground-state and low-order excitations forsparse, finite graphs are a fragmented set of isolated networkclusters. Configurations of higher energy are typically more connected. Theconnected networks of lowest energy are stretched out giving thenetwork large average distances. For the finite sizes we investigate,there are three regions—a low-energy regime of fragmented networks, anintermediate regime of stretched-out networks, and a high-energy regime ofcompact, disordered topologies. Scaling up the system size, the bordersbetween these regimes approach zero temperature algebraically, but different network-structuralquantities approach their T=0 values with different exponents. We arguethis is a, perhaps rare, example of a statistical-physics modelwhere finite sizes show a more interesting behavior than thethermodynamic limit.
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| 2. |
- Barrenäs, Fredrik, 1981, et al.
(författare)
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Network properties of complex human disease genes identified through genome-wide association studies.
- 2009
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Ingår i: PloS one. - San Francisco, CA San Francisco, CA, United StatesUnited States : Public Library of Science (PLoS). - 1932-6203. ; 4:11
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs), thereby eliminating discovery bias. PRINCIPAL FINDINGS: We derived a network of complex diseases (n = 54) and complex disease genes (n = 349) to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process. CONCLUSIONS: This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.
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| 3. |
- Holme, Petter, 1973-
(författare)
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Analyzing temporal networks in social media
- 2014
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Ingår i: Proceedings of the IEEE. - 0018-9219 .- 1558-2256. ; 102:12, s. 1922-1933
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Forskningsöversikt (refereegranskat)abstract
- Many types of social media metadata come in forms of temporal networks, networks where we have information about not only who is in contact with whom but also when contacts happen. In this paper, we review methods to analyze temporal networks developed in the last few years applied to social media data. These methods seek to identify important spreaders and, in more generality, how the temporal and topological structure of interaction affects spreading processes.
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| 4. |
- Holme, Petter, 1973-, et al.
(författare)
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Birth and death of links control disease spreading in empirical contact networks
- 2014
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 4, s. 4999-
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Tidskriftsartikel (refereegranskat)abstract
- We investigate what structural aspects of a collection of twelve empirical temporal networks of human contacts are important to disease spreading. We scan the entire parameter spaces of the two canonical models of infectious disease epidemiology-the Susceptible-Infectious-Susceptible (SIS) and Susceptible-Infectious-Removed (SIR) models. The results from these simulations are compared to reference data where we eliminate structures in the interevent intervals, the time to the first contact in the data, or the time from the last contact to the end of the sampling. The picture we find is that the birth and death of links, and the total number of contacts over a link, are essential to predict outbreaks. On the other hand, the exact times of contacts between the beginning and end, or the interevent interval distribution, do not matter much. In other words, a simplified picture of these empirical data sets that suffices for epidemiological purposes is that links are born, is active with some intensity, and die.
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| 5. |
- Holme, Petter, 1973-
(författare)
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Epidemiologically Optimal Static Networks from Temporal Network Data
- 2013
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 9:7
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Tidskriftsartikel (refereegranskat)abstract
- One of network epidemiology's central assumptions is that the contact structure over which infectious diseases propagate can be represented as a static network. However, contacts are highly dynamic, changing at many time scales. In this paper, we investigate conceptually simple methods to construct static graphs for network epidemiology from temporal contact data. We evaluate these methods on empirical and synthetic model data. For almost all our cases, the network representation that captures most relevant information is a so-called exponential-threshold network. In these, each contact contributes with a weight decreasing exponentially with time, and there is an edge between a pair of vertices if the weight between them exceeds a threshold. Networks of aggregated contacts over an optimally chosen time window perform almost as good as the exponential-threshold networks. On the other hand, networks of accumulated contacts over the entire sampling time, and networks of concurrent partnerships, perform worse. We discuss these observations in the context of the temporal and topological structure of the data sets.
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| 6. |
- Holme, Petter, 1973-
(författare)
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Extinction Times of Epidemic Outbreaks in Networks
- 2013
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 8:12
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Tidskriftsartikel (refereegranskat)abstract
- In the Susceptible–Infectious–Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out before they spread to a large fraction of people. We characterize how the maximal extinction time in SIR simulations on networks depend on the network structure. For example we find that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction. Furthermore, the transmission probability giving the longest outbreaks is larger than, but otherwise seemingly independent of, the epidemic threshold.
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| 7. |
- Holme, Petter, 1973-
(författare)
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Form and function of complex networks
- 2004
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Networks are all around us, all the time. From the biochemistry of our cells to the web of friendships across the planet. From the circuitry of modern electronics to chains of historical events. A network is the result of the forces that shaped it. Thus the principles of network formation can be, to some extent, deciphered from the network itself. All such information comprises the structure of the network. The study of network structure is the core of modern network science. This thesis centres around three aspects of network structure: What kinds of network structures are there and how can they be measured? How can we build models for network formation that give the structure of networks in the real world? How does the network structure affect dynamical systems confined to the networks? These questions are discussed using a variety of statistical, analytical and modelling techniques developed by physicists, mathematicians, biologists, chemists, psychologists, sociologists and anthropologists. My own research touches all three questions. In this thesis I present works trying to answer: What is the best way to protect a network against sinister attacks? How do groups form in friendship networks? Where do traffic jams appear in a communication network? How is cellular metabolism organised? How do Swedes flirt on the Internet? . . . and many other questions.
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| 8. |
- Holme, Petter, 1973-, et al.
(författare)
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Heterogeneous attachment strategies optimize the topology of dynamic wireless networks
- 2010
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Ingår i: European Physical Journal B. - : Springer Science and Business Media LLC. - 1434-6028 .- 1434-6036. ; 73:4, s. 597-604
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Tidskriftsartikel (refereegranskat)abstract
- In optimizing the topology of wireless networks built of a dynamic set of spatially embedded agents, there are many trade-offs to be dealt with. The network should preferably be as small (in the sense that the average, or maximal, pathlength is short) as possible, it should be robust to failures, not consume too much power, and so on. In this paper, we investigate simple models of how agents can choose their neighbors in such an environment. In our model of attachment, we can tune from one situation where agents prefer to attach to others in closest proximity, to a situation where agents attach to random others regardless of distance (which thus are, on average, further away than the connections to the spatial neighbors). We evaluate this scenario with several performance measures and find that the optimal topologies, for most of the quantities, is obtained for strategies resulting in a mix of most local and a few random connections.
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| 9. |
- Holme, Petter, 1973-
(författare)
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Model versions and fast algorithms for network epidemiology
- 2014
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Ingår i: Journal of Logistical Engineering University. - 1672-7843. ; 30:3, s. 1-7
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Tidskriftsartikel (refereegranskat)abstract
- Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreading of infectious diseases. In network epidemiology, one represents the contact structure as a network of nodes (individuals) connected by links (sometimes as a temporal network where the links are not continuously active) and the disease as a compartmental model (where individuals are assigned states with respect to the disease and follow certain transition rules between the states). In this paper, we discuss fast algorithms for such simulations and also compare two commonly used versions,one where there is a constant recovery rate (the number of individuals that stop being infectious per time is proportional to the number of such people);the other where the duration of the disease is constant. The results show that, for most practical purposes, these versions are qualitatively the same.
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| 10. |
- Holme, Petter, 1973-
(författare)
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Social, sexual and economic networks of prostitution
- 2012
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Ingår i: Leonardo. - : MIT Press. - 0024-094X .- 1530-9282. ; 45:1, s. 80-81
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Tidskriftsartikel (refereegranskat)abstract
- This article discusses the networks of prostitution, in particular those that can be extracted from online data, and what they can teach us about prostitution itself, disease spreading, cultural differences and a broader spectrum of socio-economical phenomena.
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