| 1. |
- Bohlin, Ludvig, 1986-
(författare)
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Toward higher-order network models
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Complex systems play an essential role in our daily lives. These systems consist of many connected components that interact with each other. Consider, for example, society with billions of collaborating individuals, the stock market with numerous buyers and sellers that trade equities, or communication infrastructures with billions of phones, computers and satellites.The key to understanding complex systems is to understand the interaction patterns between their components - their networks. To create the network, we need data from the system and a model that organizes the given data in a network representation. Today's increasing availability of data and improved computational capacity for analyzing networks have created great opportunities for the network approach to further prosper. However, increasingly rich data also gives rise to new challenges that question the effectiveness of the conventional approach to modeling data as a network. In this thesis, we explore those challenges and provide methods for simplifying and highlighting important interaction patterns in network models that make use of richer data.Using data from real-world complex systems, we first show that conventional network modeling can provide valuable insights about the function of the underlying system. To explore the impact of using richer data in the network representation, we then expand the analysis for higher-order models of networks and show why we need to go beyond conventional models when there is data that allows us to do so. In addition, we also present a new framework for higher-order network modeling and analysis. We find that network models that capture richer data can provide more accurate representations of many real-world complex systems.
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| 2. |
- Ahlberg, Sebastian, et al.
(författare)
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Many-body effects on tracer particle diffusion with applications for single-protein dynamics on DNA
- 2015
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Ingår i: New Journal of Physics. - : IOP Publishing. - 1367-2630. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- 30% of the DNA in E. coli bacteria is covered by proteins. Such a high degree of crowding affects the dynamics of generic biological processes (e.g. gene regulation, DNA repair, protein diffusion etc) in ways that are not yet fully understood. In this paper, we theoretically address the diffusion constant of a tracer particle in a one-dimensional system surrounded by impenetrable crowder particles. While the tracer particle always stays on the lattice, crowder particles may unbind to a surrounding bulk and rebind at another, or the same, location. In this scenario we determine how the long time diffusion constant D (after many unbinding events) depends on (i) the unbinding rate of crowder particles k(off), and (ii) crowder particle line density rho, from simulations (using the Gillespie algorithm) and analytical calculations. For small k(off), we find D similar to k(off)/rho(2) when crowder particles do not diffuse on the line, and D similar to root Dk(off)/rho when they are diffusing; D is the free particle diffusion constant. For large k(off), we find agreement with mean-field results which do not depend on k(off). From literature values of k(off) and D, we show that the small k(off) -limit is relevant for in vivo protein diffusion on crowded DNA. Our results apply to single-molecule tracking experiments.
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| 3. |
- Bernenko, Dolores, et al.
(författare)
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Exploring 3D community inconsistency in human chromosome contact networks
- 2023
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Ingår i: Journal of physics. Complexity. - : Institute of Physics (IOP). - 2632-072X. ; 4:3
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Researchers developed chromosome capture methods such as Hi-C to better understand DNA's 3D folding in nuclei. The Hi-C method captures contact frequencies between DNA segment pairs across the genome. When analyzing Hi-C data sets, it is common to group these pairs using standard bioinformatics methods (e.g., PCA). Other approaches handle Hi-C data as weighted networks, where connected node represent DNA segments in 3D proximity. In this representation, one can leverage community detection techniques developed in complex network theory to group nodes into mesoscale communities containing similar connection patterns. While there are several successful attempts to analyze Hi-C data in this way, it is common to report and study the most typical community structure. But in reality, there are often several valid candidates. Therefore, depending on algorithm design, different community detection methods focusing on slightly different connectivity features may have differing views on the ideal node groupings. In fact, even the same community detection method may yield different results if using a stochastic algorithm. This ambiguity is fundamental to community detection and shared by most complex networks whenever interactions span all scales in the network. This is known as community inconsistency. This paper explores this inconsistency of 3D communities in Hi-C data for all human chromosomes. We base our analysis on two inconsistency metrics, one local and one global, and quantify the network scales where the community separation is most variable. For example, we find that TADs are less reliable than A/B compartments and that nodes with highly variable node-community memberships are associated with open chromatin. Overall, our study provides a helpful framework for data-driven researchers and increases awareness of some inherent challenges when clustering Hi-C data into 3D communities.
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| 4. |
- Bernenko, Dolores, 1986-
(författare)
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Exploring the multiscale 3D architecture of human chromosome contact networks
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cells regulate genes to coordinate essential functions allowing cells to grow, divide, specialize, and respond to stresses. While regulatory proteins are the most common way to control these genes, the DNA’s 3D structure also plays a critical role as it affects how proteins access genes and how regulatory DNA elements interact over large genomic distances. This thesis explores the latter aspect of gene regulation by mapping DNA’s 3D multiscale architecture and exploring the within-scale variability.To study these aspects, we analyzed empirical DNA-DNA contact data from a technique known as Hi-C. This technique measures the contact frequency between pairs of points on DNA. To infer multiscale DNA 3D structures from this data set, we adopt and develop a community detection framework that finds the groups of interconnected DNA regions. Rooted in network science, this approach allowed us to study the DNA’s ensemble-averaged 3D organization while embracing its complexity and variability.In this work, we mapped DNA’s multiscale 3D architecture and demonstrated how our community detection algorithm charts the structural scales in regimes that are often opaque to other computational tools. We also addressed several specific research questions. First, we explored cross-scale 3D structures, quantifying to what extent their interactions are hierarchical. We also determined the scales where the 3D structures seem most robust and quantified the DNA's structural ambiguities. Additionally, we explored the association between DNA's 3D architecture and epigenetic states. Finally, we demonstrated how our framework applies to another DNA contact data set (HiChIP) that may be useful to better understand spatial rearrangements in cancer cells.
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| 5. |
- Bernenko, Dolores, et al.
(författare)
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Mapping the semi-nested community structure of 3D chromosome contact networks
- 2022
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Mammalian DNA folds into 3D structures that facilitate and regulate genetic processes such as transcription, DNA repair, and epigenetics. Several insights derive from chromosome capture methods, such as Hi-C, which allow researchers to construct contact maps depicting 3D interactions among all DNA segment pairs. These maps show a complex cross-scale organization spanning megabase-pair compartments to short-ranged DNA loops. To better understand the organizing principles, several groups analyzed Hi-C data assuming a Russian-doll-like nested hierarchy where DNA regions of similar sizes merge into larger and larger structures. Apart from being a simple and appealing description, this model explains, e.g., the omnipresent chequerboard pattern seen in Hi-C maps, known as A/B compartments, and foreshadows the co-localization of some functionally similar DNA regions. However, while successful, this model is incompatible with the two competing mechanisms that seem to shape a significant part of the chromosomes’ 3D organization: loop extrusion and phase separation. This paper aims to map out the chromosome’s actual folding hierarchy from empirical data. To this end, we take advantage of Hi-C experiments and treat the measured DNA-DNA interactions as a weighted network. From such a network, we extract 3D communities using the generalized Louvain algorithm. This algorithm has a resolution parameter that allows us to scan seamlessly through the community size spectrum, from A/B compartments to topologically associated domains (TADs). By constructing a hierarchical tree connecting these communities, we find that chromosomes are more complex than a perfect hierarchy. Analyzing how communities nest relative to a simple folding model, we found that chromosomes exhibit a significant portion of nested and non-nested community pairs alongside considerable randomness. In addition, by examining nesting and chromatin types, we discovered that nested parts are often associated with active chromatin. These results highlight that crossscale relationships will be essential components in models aiming to reach a deep understanding of the causal mechanisms of chromosome folding.
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| 6. |
- Bernenko, Dolores, et al.
(författare)
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Mapping the semi-nested community structure of 3D chromosome contact networks
- 2023
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 19:7
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Tidskriftsartikel (refereegranskat)abstract
- Mammalian DNA folds into 3D structures that facilitate and regulate genetic processes such as transcription, DNA repair, and epigenetics. Several insights derive from chromosome capture methods, such as Hi-C, which allow researchers to construct contact maps depicting 3D interactions among all DNA segment pairs. These maps show a complex cross-scale organization spanning megabase-pair compartments to short-ranged DNA loops. To better understand the organizing principles, several groups analyzed Hi-C data assuming a Russian-doll-like nested hierarchy where DNA regions of similar sizes merge into larger and larger structures. Apart from being a simple and appealing description, this model explains, e.g., the omnipresent chequerboard pattern seen in Hi-C maps, known as A/B compartments, and foreshadows the co-localization of some functionally similar DNA regions. However, while successful, this model is incompatible with the two competing mechanisms that seem to shape a significant part of the chromosomes' 3D organization: loop extrusion and phase separation. This paper aims to map out the chromosome's actual folding hierarchy from empirical data. To this end, we take advantage of Hi-C experiments and treat the measured DNA-DNA interactions as a weighted network. From such a network, we extract 3D communities using the generalized Louvain algorithm. This algorithm has a resolution parameter that allows us to scan seamlessly through the community size spectrum, from A/B compartments to topologically associated domains (TADs). By constructing a hierarchical tree connecting these communities, we find that chromosomes are more complex than a perfect hierarchy. Analyzing how communities nest relative to a simple folding model, we found that chromosomes exhibit a significant portion of nested and non-nested community pairs alongside considerable randomness. In addition, by examining nesting and chromatin types, we discovered that nested parts are often associated with active chromatin. These results highlight that cross-scale relationships will be essential components in models aiming to reach a deep understanding of the causal mechanisms of chromosome folding.
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| 7. |
- Bernhardsson, Sebastian, et al.
(författare)
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Structural correlations in bacterial metabolic networks
- 2011
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Ingår i: BMC Evolutionary Biology. - : Springer Science and Business Media LLC. - 1471-2148. ; 11:20
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Tidskriftsartikel (refereegranskat)abstract
- Background Evolution of metabolism occurs through the acquisition and loss of genes whose products acts as enzymes in metabolic reactions, and from a presumably simple primordial metabolism the organisms living today have evolved complex and highly variable metabolisms. We have studied this phenomenon by comparing the metabolic networks of 134 bacterial species with known phylogenetic relationships, and by studying a neutral model of metabolic network evolution. Results We consider the 'union-network' of 134 bacterial metabolisms, and also the union of two smaller subsets of closely related species. Each reaction-node is tagged with the number of organisms it belongs to, which we denote organism degree (OD), a key concept in our study. Network analysis shows that common reactions are found at the centre of the network and that the average OD decreases as we move to the periphery. Nodes of the same OD are also more likely to be connected to each other compared to a random OD relabelling based on their occurrence in the real data. This trend persists up to a distance of around five reactions. A simple growth model of metabolic networks is used to investigate the biochemical constraints put on metabolic-network evolution. Despite this seemingly drastic simplification, a 'union-network' of a collection of unrelated model networks, free of any selective pressure, still exhibit similar structural features as their bacterial counterpart. Conclusions The OD distribution quantifies topological properties of the evolutionary history of bacterial metabolic networks, and lends additional support to the importance of horizontal gene transfer during bacterial metabolic evolution where new reactions are attached at the periphery of the network. The neutral model of metabolic network growth can reproduce the main features of real networks, but we observe that the real networks contain a smaller common core, while they are more similar at the periphery of the network. This suggests that natural selection and biochemical correlations can act both to diversify and to narrow down metabolic evolution.
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| 8. |
- Durang, Xavier, et al.
(författare)
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First-passage statistics under stochastic resetting in bounded domains
- 2019
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Ingår i: Journal of Physics A. - : Institute of Physics Publishing (IOPP). - 1751-8113 .- 1751-8121. ; 52:22
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Tidskriftsartikel (refereegranskat)abstract
- We investigate the first-passage problem where a diffusive searcher stochastically resets to a fixed position at a constant rate in a bounded domain. We put forward an analytical framework for this problem where the resetting rate r, the resetting position x r , the initial position x 0, the domain size L, and the particle's diffusion constant D are independent variables. From this we obtain analytical expressions for the mean-first passage time, survival probability and the first-passage time density in Laplace space in terms of the above independent variables, and closed forms in time-domain expression in some cases. For the first-passage time distributions their full-time profiles in time-domain are numerically obtained and validated by Monte Carlo simulations. We show that for the general resetting condition the first-passage process has rich nontrivial features as it combines effects from resetting and the finiteness of the domain. A phase diagram showing the regions for resetting-enhanced and -suppressed first-passages is obtained analytically. Counter-intuitively, resetting facilitates the first-passage event even if the particle resets to a position that is further away from the target than where it started. Finally, we show that averaging over resetting positions, resetting never helps the search compared to a random search, unless the resetting position is displaced from the initial position.
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| 9. |
- Forsling, Robin, et al.
(författare)
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Non-Markovian effects in the first-passage dynamics of obstructed tracer particle diffusion in one-dimensional systems.
- 2014
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Ingår i: Journal of Chemical Physics. - : AIP Publishing. - 0021-9606 .- 1089-7690. ; 141:9
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Tidskriftsartikel (refereegranskat)abstract
- The standard setup for single-file diffusion is diffusing particles in one dimension which cannot overtake each other, where the dynamics of a tracer (tagged) particle is of main interest. In this article, we generalize this system and investigate first-passage properties of a tracer particle when flanked by identical crowder particles which may, besides diffuse, unbind (rebind) from (to) the one-dimensional lattice with rates koff (kon). The tracer particle is restricted to diffuse with rate kD on the lattice and the density of crowders is constant (on average). The unbinding rate koff is our key parameter and it allows us to systematically study the non-trivial transition between the completely Markovian case (koff ≫ kD) to the non-Markovian case (koff ≪ kD) governed by strong memory effects. This has relevance for several quasi one-dimensional systems. One example is gene regulation where regulatory proteins are searching for specific binding sites on a crowded DNA. We quantify the first-passage time distribution, f (t) (t is time), numerically using the Gillespie algorithm, and estimate f (t) analytically. In terms of koff (keeping kD fixed), we study the transition between the two known regimes: (i) when koff ≫ kD the particles may effectively pass each other and we recover the single particle result f (t) ∼ t(-3/2), with a reduced diffusion constant; (ii) when koff ≪ kD unbinding is rare and we obtain the single-file result f (t) ∼ t(-7/4). The intermediate region displays rich dynamics where both the characteristic f (t) - peak and the long-time power-law slope are sensitive to koff.
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| 10. |
- Hedström, Lucas, et al.
(författare)
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Modelling chromosome-wide target search
- 2023
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Ingår i: New Journal of Physics. - : Institute of Physics (IOP). - 1367-2630. ; 25:3
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Tidskriftsartikel (refereegranskat)abstract
- The most common gene regulation mechanism is when a transcription factor (TF) protein binds to a regulatory sequence to increase or decrease RNA transcription. However, TFs face two main challenges when searching for these sequences. First, the sequences are vanishingly short relative to the genome length. Second, there are many nearly identical sequences scattered across the genome, causing proteins to suspend the search. But as pointed out in a computational study of LacI regulation in Escherichia coli, such almost-targets may lower search times if considering DNA looping. In this paper, we explore if this also occurs over chromosome-wide distances. To this end, we developed a cross-scale computational framework that combines established facilitated-diffusion models for basepair-level search and a network model capturing chromosome-wide leaps. To make our model realistic, we used Hi-C data sets as a proxy for 3D proximity between long-ranged DNA segments and binding profiles for more than 100 TFs. Using our cross-scale model, we found that median search times to individual targets critically depend on a network metric combining node strength (sum of link weights) and local dissociation rates. Also, by randomizing these rates, we found that some actual 3D target configurations stand out as considerably faster or slower than their random counterparts. This finding hints that chromosomes’ 3D structure funnels essential TFs to relevant DNA regions.
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