1. |
- Eriksen, K.A., et al.
(author)
-
Scale-free growing networks imply linear preferential attachment
- 2002
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In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. - 1539-3755. ; 65:1
-
Journal article (peer-reviewed)abstract
- It has been recognized for some time that a network grown by the addition of nodes with linear preferential attachment will possess a scale-free distribution of connectivities. Here we prove by some analytical arguments that the linearity is a necessary component to obtain this kind of distribution. However, the preferential linking rate does not necessarily apply to single nodes, but to groups of nodes of the same connectivity. We also point out that for a time-varying mean connectivity the linking rate will deviate from a linear expression by an extra asymptotically logarithmic term. © 2001 The American Physical Society.
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2. |
- Eriksen, K. A., et al.
(author)
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Visualization of large-scale correlations in gene expressions
- 2004
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In: Functional & Integrative Genomics. - : Springer Science and Business Media LLC. - 1438-793X .- 1438-7948. ; 4:4, s. 241-245
-
Journal article (peer-reviewed)abstract
- Large-scale expression data are today measured for several thousands of genes simultaneously. Furthermore, most genes are being categorized according to their properties. This development has been followed by an exploration of theoretical tools to integrate these diverse data types. A key problem is the large noise-level in the data. Here, we investigate ways to extract the remaining signals within these noisy data sets. We find large-scale correlations within data from Saccharomyces cerevisiae with respect to properties of the encoded proteins. These correlations are visualized in a way that is robust to the underlying noise in the measurement of the individual gene expressions. In particular, for S. cerevisiae we observe that the proteins corresponding to the 400 highest expressed genes typically are localized to the cytoplasm. These most expressed genes are not essential for cell survival.
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3. |
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4. |
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5. |
- Gustafsson, Mika, 1977-, et al.
(author)
-
Comparison and validation of community structures in complex networks
- 2006
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In: Physica A. - : Elsevier BV. - 0378-4371 .- 1873-2119. ; 367, s. 559-576
-
Journal article (peer-reviewed)abstract
- The issue of partitioning a network into communities has attracted a great deal of attention recently. Most authors seem to equate this issue with the one of finding the maximum value of the modularity, as defined by Newman. Since the problem formulated this way is believed to be NP-hard, most effort has gone into the construction of search algorithms, and less to the question of other measures of community structures, similarities between various partitionings and the validation with respect to external information.Here we concentrate on a class of computer generated networks and on three well-studied real networks which constitute a bench-mark for network studies; the karate club, the US college football teams and a gene network of yeast. We utilize some standard ways of clustering data (originally not designed for finding community structures in networks) and show that these classical methods sometimes outperform the newer ones. We discuss various measures of the strength of the modular structure, and show by examples features and drawbacks. Further, we compare different partitions by applying some graph-theoretic concepts of distance, which indicate that one of the quality measures of the degree of modularity corresponds quite well with the distance from the true partition. Finally, we introduce a way to validate the partitionings with respect to external data when the nodes are classified but the network structure is unknown. This is here possible since we know everything of the computer generated networks, as well as the historical answer to how the karate club and the football teams are partitioned in reality. The partitioning of the gene network is validated by use of the Gene Ontology database, where we show that a community in general corresponds to a biological process.
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6. |
- Gustafsson, Mika, 1977-, et al.
(author)
-
Constructing and analyzing a large-scale gene-to-gene regulatory network Lasso-constrained inference and biological validation
- 2005
-
In: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964. ; 2:3, s. 254-261
-
Journal article (peer-reviewed)abstract
- We construct a gene-to-gene regulatory network from time-series data of expression levels for the whole genome of the yeast Saccharomyces cerevisae, in a case where the number of measurements is much smaller than the number of genes in the network. This network is analyzed with respect to present biological knowledge of all genes (according to the Gene Ontology database), and we find some of its large-scale properties to be in accordance with known facts about the organism. The linear modeling employed here has been explored several times, but due to lack of any validation beyond investigating individual genes, it has been seriously questioned with respect to its applicability to biological systems. Our results show the adequacy of the approach and make further investigations of the model meaningful.
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7. |
- Gustafsson, Mika, 1977-, et al.
(author)
-
Gene Expression Prediction by Soft Integration and the Elastic Net : Best Performance of the DREAM3 Gene Expression Challenge
- 2010
-
In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 5:2, s. e9134-
-
Journal article (peer-reviewed)abstract
- Background: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance.Methodology/Principal Findings: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the “elastic net”. Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance.Conclusions/Significance: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.
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8. |
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9. |
- Gustafsson, Mika, 1977-
(author)
-
Gene networks from high-throughput data : Reverse engineering and analysis
- 2010
-
Doctoral thesis (other academic/artistic)abstract
- Experimental innovations starting in the 1990’s leading to the advent of high-throughput experiments in cellular biology have made it possible to measure thousands of genes simultaneously at a modest cost. This enables the discovery of new unexpected relationships between genes in addition to the possibility of falsify existing. To benefit as much as possible from these experiments the new inter disciplinary research field of systems biology have materialized. Systems biology goes beyond the conventional reductionist approach and aims at learning the whole system under the assumption that the system is greater than the sum of its parts. One emerging enterprise in systems biology is to use the high-throughput data to reverse engineer the web of gene regulatory interactions governing the cellular dynamics. This relatively new endeavor goes further than clustering genes with similar expression patterns and requires the separation of cause of gene expression from the effect. Despite the rapid data increase we then face the problem of having too few experiments to determine which regulations are active as the number of putative interactions has increased dramatic as the number of units in the system has increased. One possibility to overcome this problem is to impose more biologically motivated constraints. However, what is a biological fact or not is often not obvious and may be condition dependent. Moreover, investigations have suggested several statistical facts about gene regulatory networks, which motivate the development of new reverse engineering algorithms, relying on different model assumptions. As a result numerous new reverse engineering algorithms for gene regulatory networks has been proposed. As a consequent, there has grown an interest in the community to assess the performance of different attempts in fair trials on “real” biological problems. This resulted in the annually held DREAM conference which contains computational challenges that can be solved by the prosing researchers directly, and are evaluated by the chairs of the conference after the submission deadline.This thesis contains the evolution of regularization schemes to reverse engineer gene networks from high-throughput data within the framework of ordinary differential equations. Furthermore, to understand gene networks a substantial part of it also concerns statistical analysis of gene networks. First, we reverse engineer a genome-wide regulatory network based solely on microarray data utilizing an extremely simple strategy assuming sparseness (LASSO). To validate and analyze this network we also develop some statistical tools. Then we present a refinement of the initial strategy which is the algorithm for which we achieved best performer at the DREAM2 conference. This strategy is further refined into a reverse engineering scheme which also can include external high-throughput data, which we confirm to be of relevance as we achieved best performer in the DREAM3 conference as well. Finally, the tools we developed to analyze stability and flexibility in linearized ordinary differential equations representing gene regulatory networks is further discussed.
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10. |
- Gustafsson, Mika, et al.
(author)
-
Genome-wide system analysis reveals stable yet flexible network dynamics in yeast
- 2009
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In: IET SYSTEMS BIOLOGY. - : Institution of Engineering and Technology (IET). - 1751-8849 .- 1751-8857. ; 3:4, s. 219-228
-
Journal article (peer-reviewed)abstract
- Recently, important insights into static network topology for biological systems have been obtained, but still global dynamical network properties determining stability and system responsiveness have not been accessible for analysis. Herein, we explore a genome-wide gene-to-gene regulatory network based on expression data from the cell cycle in Saccharomyces cerevisae (budding yeast). We recover static properties like hubs (genes having several out-going connections), network motifs and modules, which have previously been derived from multiple data sources such as whole-genome expression measurements, literature mining, protein-protein and transcription factor binding data. Further, our analysis uncovers some novel dynamical design principles; hubs are both repressed and repressors, and the intra-modular dynamics are either strongly activating or repressing whereas inter-modular couplings are weak. Finally, taking advantage of the inferred strength and direction of all interactions, we perform a global dynamical systems analysis of the network. Our inferred dynamics of hubs, motifs and modules produce a more stable network than what is expected given randomised versions. The main contribution of the repressed hubs is to increase system stability, while higher order dynamic effects (e.g. module dynamics) mainly increase system flexibility. Altogether, the presence of hubs, motifs and modules induce few flexible modes, to which the network is extra sensitive to an external signal. We believe that our approach, and the inferred biological mode of strong flexibility and stability, will also apply to other cellular networks and adaptive systems.
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11. |
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12. |
- Gustafsson, Mika, et al.
(author)
-
Integrating various data sources for improved quality in reverse engineering of gene regulatory networks
- 2009. - 1
-
In: Handbook of Research on Computational Methodologies in Gene Regulatory Networks. - : IGI Global. - 9781605666853 - 9781605666860 ; , s. 476-496
-
Book chapter (other academic/artistic)abstract
- In this chapter we outline a methodology to reverse engineer GRNs from various data sources within an ODE framework. The methodology is generally applicable and is suitable to handle the broad error distribution present in microarrays. The main effort of this chapter is the exploration of a fully data driven approach to the integration problem in a “soft evidence” based way. Integration is here seen as the process of incorporation of uncertain a priori knowledge and is therefore only relied upon if it lowers the prediction error. An efficient implementation is carried out by a linear programming formulation. This LP problem is solved repeatedly with small modifications, from which we can benefit by restarting the primal simplex method from nearby solutions, which enables a computational efficient execution. We perform a case study for data from the yeast cell cycle, where all verified genes are putative regulators and the a priori knowledge consists of several types of binding data, text-mining and annotation knowledge.
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13. |
- Gustafsson, Mika, et al.
(author)
-
Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions
- 2009
-
In: CHALLENGES OF SYSTEMS BIOLOGY: COMMUNITY EFFORTS TO HARNESS BIOLOGICAL COMPLEXITY. - : Wiley. - 0077-8923 .- 1749-6632. ; 1158, s. 265-275
-
Journal article (peer-reviewed)abstract
- The quest to determine cause from effect is often referred to as reverse engineering in the context of cellular networks. Here we propose and evaluate an algorithm for reverse engineering a gene regulatory network from time-series kind steady-state data. Our algorithmic pipeline, which is rather standard in its parts but not in its integrative composition, combines ordinary differential equations, parameter estimations by least angle regression, and cross-validation procedures for determining the in-degrees and selection of nonlinear transfer functions. The result of the algorithm is a complete directed net-work, in which each edge has been assigned a score front it bootstrap procedure. To evaluate the performance, we submitted the outcome of the algorithm to the reverse engineering assessment competition DREAM2, where we used the data corresponding to the InSillico1 and InSilico2 networks as input. Our algorithm outperformed all other algorithms when inferring one of the directed gene-to-gene networks.
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14. |
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15. |
- Gustafsson, Mika, et al.
(author)
-
System Analysis of Gene Regulatory Networks
-
Other publication (other academic/artistic)abstract
- The inference of genome-wide regulatory networks in cells from high-throughput data sets has revealed a diverse picture of only partly overlapping descriptions. Nevertheless, several conclusions of the large-scale properties in the organization of these networks are possible. For example, the presence of hubs, a modular structure and certain motifs are recurrent phenomena. Several authors have recently claimed cell systems to be stable against perturbations and random errors, but still able to rapidly switch between different states from specific stimuli. Since inferred genome-wide systems need to be extremely simple to avoid overfitting, these two features are hard to attain simultaneously in a mathematical model. Here we review and discuss possible measures of how system stability and flexibility may be manifested and measured for linear ODE models. Furthermore, we review how different network properties contribute to these systems level properties. It turns out that the presence of repressed hubs, together with other phenomena of topological nature such as motifs and modules, contributes to the overall stability and/or flexibility of the system.
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16. |
- Hörnquist, Michael, 1969-
(author)
-
A periodically Ordered Structures in One Dimension
- 1999
-
Doctoral thesis (other academic/artistic)abstract
- This thesis deals with different aspects of aperiodically ordered structures in one dimension. The approach is entirely theoretical, and the models used have various relevance for real systems. The main objective is to make a general study of how the solutions to some well-known equations behave when they are used to describe physical phenomena in structures which are aperiodically ordered.To obtain structures that are in some sense generic for aperiodic order, we use different sequences such as the Fibonacci sequence, the Thue-Morse sequence, the period-doubling sequence, the Rudin-Shapiro sequence, etc. We let some physical entities, such as on-site potentials or atomic masses, be ordered according to these sequences.One system studied is a tight-binding Schrödinger equation where the on-site potentialis modulated by some different circle sequences. It is found that for almost all such sequences related to the precious means, the electron spectra are purely singular continuous and of zero Lebesgue measure. A closely related study is for chains of aperiodically ordered quantum dots. The systems are modelled by a Kronig-Penney potential, and we calculate their conductance as a function of the Fermi level for realistic dimensions of such chains. We find some signs that we interpret as fingerprints of the singular continuous spectra these models possess in the limit of an infinite number of dots.Inspired by the fact that proteins can be considered as aperiodic chains and the somewhat successful attempts to classify their folding properties by use of the methods of block variables, we apply the same concept to some different deterministic aperiodic sequences. There turns out, however, to be no direct correspondence between the behaviour of the block variables and other properties of the sequences.The rest of the studies are about phenomena that need nonlinear terms in the equations for their description. One study is for how the wavefunction for an initially localized polaron in an aperiodically ordered lattice will spread. The governing equation we use is the discrete nonlinear Schrödinger equation (DNLS). We find that for a large enough nonlinearity, the probability of finding the quasiparticle at the initial site will always be nonzero and the participation number finite for all systems under study (self-trapping). For potentials yielding a singular continuous energy spectrum in the linear limit, selftrapping seems to appear for arbitrarily small nonlinearities. We also find that the root-mean-square width of the wave packet will increase infinitely with time for those of the studied systems which have a continuous part in their linear energy spectra, even when self-trapping has occurred.Another study is for arrays of Josephson junctions, described by the perturbed discrete sine-Gordon equation. The junctions are of two different kinds and ordered aperiodically but equidistantly. We study the dynamics of a single fluxon in such a lattice.With the use of an effective potential we explain the behaviour of the fluxon when it gets pinned in different arrays. The potential also gives a qualitative understanding of the deviation of the velocity of a propagating fluxon compared with an earlier obtained formula. It turns out that the self-similarity of the underlying sequences is important for the detailed dynamics, but not for the speed of a propagating fluxon.Finally there are investigations of various aspects of lattice dynamics when the atoms in the lattice have two different masses ( diatomic lattices) and are ordered according to some of the sequences mentioned above. This time we use classical mechanics to obtain the governing equations of motion.A study of solitary wave propagation in aperiodically ordered diatomic Tod a lattices reveals that the damping is considerable less for these systems than for a random lattice. The short range correlation between the atoms in the aperiodic lattices seems to be of main importance for how much the wave is damped. We suggest therefore that the entropy according to Shannon might be a relevant measure for the properties of the lattices in this case. It is shown that this measure yields at least an approximative agreement with what is actually achieved by our numerical experiments.The anharmonic terms in the potentials used can give rise to localized modes in lattices which only have extended modes in the harmonic approximation. This intrinsic localization is often referred to as discrete breathers. We find such modes numerically in some aperiodically ordered diatomic lattices in two different ways. The first method is known as the rotating wave approximation, which essentially means that we discard all harmonics except the one of lowest frequency. The second method is the use of the anti-continuous limit, which in this case refers to when the larger mass-value is infinite. In this limit, the system is integrable and one can find a solution to the equations of motion. This solution is then continued by the implicit function theorem to finite values of the larger mass.In analogy with the polaron study mentioned above, we also study the same phenomena for these classical models and energy localization. This means that we excite a few sites in the lattice and follow how the energy will spread in the system as time proceeds. We find the propagation to be correlated to the underlying dispersion relation and to the nature of the phase space for a reduced system.
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17. |
- Hörnquist, Michael, et al.
(author)
-
Discrete breathers in aperiodic diatomic FPU lattices with long range order
- 2000
-
In: Physica D. - 0167-2789 .- 1872-8022. ; 136:1-2, s. 93-124
-
Journal article (peer-reviewed)abstract
- This study presents various aspects of discrete breathers in diatomic FPU lattices with masses varying according to the aperiodic Fibonacci and Thue-Morse sequences. We investigate the existence of time-periodic breathers, starting from the anti-continuous limit and consider excitations of isolated light atoms, hence obtaining the domain of unique existence for these breathers. We also perform a linear stability analysis by studying the Floquet operator. The found exact solutions are used, slightly perturbed, as initial conditions for long-time simulations of the breathers. These breathers turn out to be robust. Finally we consider how initial excitations of two consecutive light atoms evolve. Depending on the properties of the phase space for the two-atom system at the anti-continuous limit, we obtain different behaviour of these excitations. Especially we find that the aperiodic lattices can support localized excitations with a continuous frequency distribution for the timescales we consider, while a periodic lattice is unable to. These excitations are referred to as chaotic breathers. (C)2000 Elsevier Science B.V. All rights reserved.
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18. |
- Hörnquist, Michael, et al.
(author)
-
Effective dimensionality for principal component analysis of time series expression data
- 2003
-
In: Biosystems (Amsterdam. Print). - 0303-2647 .- 1872-8324. ; 71:3, s. 311-317
-
Journal article (peer-reviewed)abstract
- Large-scale expression data are today measured for thousands of genes simultaneously. This development has been followed by an exploration of theoretical tools to get as much information out of these data as possible. Several groups have used principal component analysis (PCA) for this task. However, since this approach is data-driven, care must be taken in order not to analyze the noise instead of the data. As a strong warning towards uncritical use of the output from a PCA, we employ a newly developed procedure to judge the effective dimensionality of a specific data set. Although this data set is obtained during the development of rat central nervous system, our finding is a general property of noisy time series data. Based on knowledge of the noise-level for the data, we find that the effective number of dimensions that are meaningful to use in a PCA is much lower than what could be expected from the number of measurements. We attribute this fact both to effects of noise and the lack of independence of the expression levels. Finally, we explore the possibility to increase the dimensionality by performing more measurements within one time series, and conclude that this is not a fruitful approach. © 2003 Elsevier Ireland Ltd. All rights reserved.
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19. |
- Hörnquist, Michael, et al.
(author)
-
Effective dimensionality of large-scale expression data using principal component analysis
- 2002
-
In: Biosystems (Amsterdam. Print). - 0303-2647 .- 1872-8324. ; 65:2-3, s. 147-156
-
Journal article (peer-reviewed)abstract
- Large-scale expression data are today measured for thousands of genes simultaneously. This development is followed by an exploration of theoretical tools to get as much information out of these data as possible. One line is to try to extract the underlying regulatory network. The models used thus far, however, contain many parameters, and a careful investigation is necessary in order not to over-fit the models. We employ principal component analysis to show how, in the context of linear additive models, one can get a rough estimate of the effective dimensionality (the number of information-carrying dimensions) of large-scale gene expression datasets. We treat both the lack of independence of different measurements in a time series and the fact that that measurements are subject to some level of noise, both of which reduce the effective dimensionality and thereby constrain the complexity of models which can be built from the data. Copyright © 2002 Elsevier Science Ireland Ltd.
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20. |
- Hörnquist, Michael, 1969-, et al.
(author)
-
Stability and Flexibility from a System Analysis of Gene RegulatoryNetworks Based on Ordinary Differential Equations
- 2011
-
In: The Open Bioinformatics Journal. - : Bentham Open. - 1875-0362. ; 5, s. 26-33
-
Journal article (peer-reviewed)abstract
- The inference of large-scale gene regulatory networks from high-throughput data sets has revealed a diverse picture of only partially overlapping descriptions. Nevertheless, several properties in the organization of these networks are recurrent, such as hubs, a modular structure and certain motifs. Several authors have recently claimed cell systems to be stable against perturbations and random errors, but still able to rapidly switch between different states from specific stimuli. Since inferred mathematical models of large-scale systems need to be extremely simple to avoid overfitting, these two features are hard to attain simultaneously for a model. Here we review and discuss possible measures of how system stability and flexibility may be manifested and measured for linearized models based on systems of ordinary differential equations. Furthermore, we review how the network properties mentioned above together with the nature of the interactions contribute to these systems level properties. It turns out that the presence of repressed hubs, together with other phenomena of topological nature such as motifs and modules, contribute to the overall stability and/or flexibility of the model.
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21. |
- Jäder, Jonas
(author)
-
Elevers möjligheter till lärande av matematiska resonemang
- 2015
-
Licentiate thesis (other academic/artistic)abstract
- En av anledningarna till varför elever har svårigheter med matematik i skolan är att utantillinlärning utgör grunden för utbildningen för många av eleverna. Procedurella och konceptuella kunskaper behövs för att skapa en bred matematisk kompetens. Eleverna lär sig bara det som de får en möjlighet att lära sig, vilket innebär att de möjligheter till lärande som erbjuds eleverna i skolan måste beaktas. Ett väletablerat ramverk som gör det möjligt attanalysera de resonemang som krävs för att lösa läroboksuppgifter samt de resonemang som används av eleverna vid uppgiftslösning har använts för att undersöka möjligheterna att lära sig resonera matematiskt. Genom att använda ramverket möjliggörs en mer förfinad diskussion av vilken typ av kunskap som används av eleverna. Ramverket skiljer på kreativa matematiska resonemang, där en lösning måste skapas av eleven, och imitativa resonemang som bygger på utantillinlärning eller imitering av en tillgänglig lösningsalgoritm. Möjligheterna att lära sig beror på klassrummets normer som har förhandlats fram mellan elever och lärare. Dessa normer påverkas i sin tur av flera faktorer. I denna avhandling diskuteras läroboken, både som en, av flera bilder, av undervisningen och utifrån hur den används i klassrummet, samt elevernas uppfattningar om matematik. I avhandlingen ingår tre studier. Den första studien består av en analys av uppgifterna, med avseende på kraven på resonemang, i läromedel från tolv länder, i fem världsdelar. I den andra studien har elevers resonemang då de arbetar med uppgifter från läroboken i klassrummet analyserats. I den tredje studien används en tematisk analys för att undersöka de uppfattningar som eleverna visar upp, vilka sedan kopplas till de resonemang som används. Resultaten visar att läroböckerna från tolv olika länder har en liknande andelen uppgifter som kräver att eleverna använder kreativa matematiska resonemang. I genomsnitt krävde ungefär var tionde uppgift ett mer genomgripande kreativt matematiskt resonemang. Resultaten visaräven att elever i den svenska gymnasieskolan främst löser de första, lättare uppgifterna, där andelen uppgifter som kräver ett kreativt matematiskt resonemang är lägre. Eleverna använder också i stor utsträckning imitativa resonemang. Möjligheterna för elever att träna sig på kreativa matematiska resonemang verkar utifrån mina resultat vara begränsade. Då elever guidar varandra genom uppgiftslösning verkar det som att fokus främst ligger på att komma fram till ett svar som överensstämmer med facit. Inte heller då elever får hjälp av en lärare verkar möjligheter till annat än imitativa resonemang skapas. Eleverna indikerar dessutom uppfattningar om att matematiska uppgifter i de allra flesta fall ska kunna lösas genom ett imitativt resonemang och att utantillinlärning därför bör vara en central del av undervisningen. Lärarens roll i klassrummet är viktig för att skapa och utveckla de gemensamma klassrumsnormerna. Stor vikt bör läggas vid vilka uppgifter och vilka läromedel som används i undervisningen. Även elevernas sätt att arbeta i klassrummet måste beaktas i relation till möjligheterna till lärande, och den matematiska förståelsen bör spela en större roll.
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22. |
- Karlsson, Fredrik, et al.
(author)
-
Order or chaos in Boolean gene networks depends on the mean fraction of canalizing functions
- 2007
-
In: Physica A. - : Elsevier BV. - 0378-4371 .- 1873-2119. ; 384:2, s. 747-757
-
Journal article (peer-reviewed)abstract
- We explore the connection between order/chaos in Boolean networks and the naturally occurring fraction of canalizing functions in such systems. This fraction turns out to give a very clear indication of whether the system possesses ordered or chaotic dynamics, as measured by Derrida plots, and also the degree of order when we compare different networks with the same number of vertices and edges. By studying also a wide distribution of indegrees in a network, we show that the mean probability of canalizing functions is a more reliable indicator of the type of dynamics for a finite network than the classical result on stability relating the bias to the mean indegree. Finally, we compare by direct simulations two biologically derived networks with networks of similar sizes but with power-law and Poisson distributions of indegrees, respectively. The biologically motivated networks are not more ordered than the latter, and in one case the biological network is even chaotic while the others are not. © 2007 Elsevier B.V. All rights reserved.
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23. |
- Lennholm, Erik, et al.
(author)
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Revisiting Salerno's sine-Gordon model of DNA : Active regions and robustness
- 2003
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In: Physica D. - 0167-2789 .- 1872-8022. ; 177:1-4, s. 233-241
-
Journal article (peer-reviewed)abstract
- We return to a simple model of DNA-transcription, first investigated by Salerno more than 10 years ago. One conjecture that time was that the promoter-regions were "dynamically active" in the sense that a stationary kink solution to the discrete sine-Gordon equation spontaneously starts to move when positioned in certain regions. Here we explore the whole genome of the bacteriophage T7, which is the same that was used in the first studies. We find that the regions in the promoters where the DNA-binding molecules attach have no special significance, while the start of the RNA-coding regions are dynamically active on a significant level. The results are checked to be robust by imposing an external disturbance in the form of a thermostat, simulating a constant temperature. © 2002 Elsevier Science B.V. All rights reserved.
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24. |
- Lombardi, Anna, 1965-, et al.
(author)
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Controllability analysis of networks
- 2007
-
In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics. - 1063-651X .- 1095-3787. ; 75:056110
-
Journal article (peer-reviewed)abstract
- The concept of controllability of linear systems from control theory is applied to networks inspired by biology. A node is in this context controllable if an external signal can be applied which can adjust the level (e.g., protein concentration) of the node in a finite time to an arbitrary value, regardless of the levels of the other nodes. The property of being downstream of the node to which the input is applied turns out to be a necessary but not a sufficient condition for being controllable. An interpretation of the controllability matrix, when applied to networks, is also given. Finally, two case studies are provided in order to better explain the concepts, as well as some results for a gene regulatory network of fission yeast.
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25. |
- Sidenvall, Johan, 1974-
(author)
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Att lära sig resonera : om elevers möjligheter att lära sig matematiska resonemang
- 2015
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Licentiate thesis (other academic/artistic)abstract
- Students only learn what they get the opportunity to learn. This means, for example, that students do not develop their reasoning- and problem solving competence unless teaching especially focuses on developing these competencies. Despite the fact that it has for the last 20 years been pointed out the need for a reform-oriented mathematics education, research still shows that in Sweden, as well as internationally, an over-emphasis are placed on rote learning and procedures, at the cost of promoting conceptual understanding. Mathematical understanding can be separated into procedural and conceptual understanding, where conceptual understanding can be connected to a reform oriented mathematics education. By developing a reasoning competence conceptual understanding can also be developed. This thesis, which deals with students’ opportunities to learn to reason mathematically, includes three studies (with data from Swedish upper secondary school, year ten and mathematics textbooks from twelve countries). These opportunities have been studied based on a textbook analysis and by studying students' work with textbook tasks during normal classroom work. Students’ opportunities to learn to reason mathematically have also been studied by examining the relationship between students' reasoning and their beliefs. An analytical framework (Lithner, 2008) has been used to categorise and analyse reasoning used in solving tasks and required to solve tasks.Results support previous research in that teaching and mathematics textbooks are not necessarily in harmony with reform-oriented mathematics teaching. And that students indicated beliefs of insecurity, personal- and subject expectations as well as intrinsic- and extrinsic motivation connects to not using mathematical reasoning when solving non-routine tasks. Most commonly students used other strategies than mathematical reasoning when solving textbook tasks. One common way to solve tasks was to be guided, in particular by another student. The results also showed that the students primarily worked with the simpler tasks in the textbook. These simpler tasks required mathematical reasoning more rarely than the more difficult tasks. The results also showed a negative relationship between a belief of insecurity and the use of mathematical reasoning. Furthermore, the results show that the distributions of tasks that require mathematical reasoning are relatively similar in the examined textbooks across five continents.Based on the results it is argued for a teaching based on sociomathematical norms that leads to an inquiry based teaching and textbooks that are more in harmony with a reform-oriented mathematics education.
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26. |
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27. |
- Thorsson, Vesteinn, et al.
(author)
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Reverse engineering galactose regulation in yeast through model selection
- 2005
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In: Statistical Applications in Genetics and Molecular Biology. - 1544-6115 .- 1544-6115. ; 4:1
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Journal article (peer-reviewed)abstract
- We examine the application of statistical model selection methods to reverse-engineering the control of galactose utilization in yeast from DNA microarray experiment data. In these experiments, relationships among gene expression values are revealed through modifications of galactose sugar level and genetic perturbations through knockouts. For each gene variable, we select predictors using a variety of methods, taking into account the variance in each measurement. These methods include maximization of log-likelihood with Cp, AIC, and BIC penalties, bootstrap and cross-validation error estimation, and coefficient shrinkage via the Lasso. Copyright ©2005 by the authors. All rights reserved.
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28. |
- Visuttijai, Kittichate, 1979-, et al.
(author)
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Lowered Expression of Tumor Suppressor Candidate MYO1C Stimulates Cell Proliferation, Suppresses Cell Adhesion and Activates AKT
- 2016
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In: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 11:10
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Journal article (peer-reviewed)abstract
- Myosin-1C (MYO1C) is a tumor suppressor candidate located in a region of recurrent losses distal to TP53. Myo1c can tightly and specifically bind to PIP2, the substrate of Phosphoinositide 3-kinase (PI3K), and to Rictor, suggesting a role for MYO1C in the PI3K pathway. This study was designed to examine MYO1C expression status in a panel of well-stratified endometrial carcinomas as well as to assess the biological significance of MYO1C as a tumor suppressor in vitro. We found a significant correlation between the tumor stage and lowered expression of MYO1C in endometrial carcinoma samples. In cell transfection experiments, we found a negative correlation between MYO1C expression and cell proliferation, and MYO1C silencing resulted in diminished cell migration and adhesion. Cells expressing excess of MYO1C had low basal level of phosphorylated protein kinase B (PKB, a.k.a. AKT) and cells with knocked down MYO1C expression showed a quicker phosphorylated AKT (pAKT) response in reaction to serum stimulation. Taken together the present study gives further evidence for tumor suppressor activity of MYO1C and suggests MYO1C mediates its tumor suppressor function through inhibition of PI3K pathway and its involvement in loss of contact inhibition.
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29. |
- Werner, Maria, 1978-
(author)
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Gene regulation models of viral genetic switches
- 2007
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Licentiate thesis (other academic/artistic)abstract
- The recent decades of research in molecular biology have resulted in break-throughs concerning our knowledge of the genetic code, protein structures and functions of the different cellular components. With this new information follows an increased interest in constructing computational models of the biological systems. A computational model can range from a description of one specific protein to a complete cell or organism. The aim of a computational model is often to complement the experimental studies and help identify essential mechanisms of a system. All processes taking place in our cells, from general metabolic processes to cell specific actions, originates from information encoded in our DNA. The first step in transferring the genetic information to a functional protein or RNA, is through the transcription of a gene. The transcription process is controlled by cellular proteins binding to DNA regions called promoters. The term "genetic switch", used in the title of this thesis, refers to a specific change in transcription activity, where one or several promoters get activated or silenced. In this thesis, I present studies of the regulation mechanisms in two different genetic switches. The first is a switch between two central promoters in the Epstein- Barr virus. This human virus is mostly known for causing the ’kissing disease’, but is also coupled to several cancer types. Infected cells can change between a resting and a proliferating phenotype, depending on which viral promoter is active. In order to understand what causes uncontrolled proliferation in tumors, it is important to understand the regulation of these viral promoters. The other switch is present in the phage λ, a bacterial virus. This virus has one specific promoter region, controlling expression of two proteins that determine if the phage will remain silent (lysogenic) in the host cell, or start producing new viral particles (go lytic). For the Epstein- Barr virus we tested, and confirmed, the hypothesis that the regulation of the two central promoters can be obtained by only one viral and one human protein. Further, we studied the cooperative effects on one of the promoters, showing that steric hindrance at the promoter region results in a more effective switching than with only cooperative binding present. For the bacteriophage λ we studied the genetically altered λ- Lac mutants, presented by Little & Atsumi in 2006. We demonstrate that the experimental results cannot, in terms of its equilibria, be explained by the mechanisms generally believed to be in control of the lysogenic/ lytic switch.
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