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  • 1. Ali, Raja H.
    et al.
    Bark, Mikael
    Miró, Jorge
    Muhammad, Sayyed A.
    Sjöstrand, Joel
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Swedish e-Science Research Centre, Sweden.
    Zubair, Syed M.
    Abbas, Raja M.
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Swedish e-Science Research Centre, Sweden.
    VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces2017In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 18, article id 97Article in journal (Refereed)
    Abstract [en]

    Background: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical difficulties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters.

    Results: We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines.

    Conclusions: VMCMC is a free software available under the New BSD License. Executable jar files, tutorial manual and source code can be downloaded from https://bitbucket. org/rhali/visualmcmc/.

  • 2. Ali, Raja H.
    et al.
    Muhammad, Sayyed A.
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Swedish e-Science Research Centre, Sweden.
    GenFamClust: an accurate, synteny-aware and reliable homology inference algorithm2016In: BMC Evolutionary Biology, E-ISSN 1471-2148, Vol. 16, article id 120Article in journal (Refereed)
    Abstract [en]

    Background: Homology inference is pivotal to evolutionary biology and is primarily based on significant sequence similarity, which, in general, is a good indicator of homology. Algorithms have also been designed to utilize conservation in gene order as an indication of homologous regions. We have developed GenFamClust, a method based on quantification of both gene order conservation and sequence similarity. Results: In this study, we validate GenFamClust by comparing it to well known homology inference algorithms on a synthetic dataset. We applied several popular clustering algorithms on homologs inferred by GenFamClust and other algorithms on a metazoan dataset and studied the outcomes. Accuracy, similarity, dependence, and other characteristics were investigated for gene families yielded by the clustering algorithms. GenFamClust was also applied to genes from a set of complete fungal genomes and gene families were inferred using clustering. The resulting gene families were compared with a manually curated gold standard of pillars from the Yeast Gene Order Browser. We found that the gene-order component of GenFamClust is simple, yet biologically realistic, and captures local synteny information for homologs. Conclusions: The study shows that GenFamClust is a more accurate, informed, and comprehensive pipeline to infer homologs and gene families than other commonly used homology and gene-family inference methods.

  • 3. Ali, Raja Hashim
    et al.
    Muhammad, Sayyed Auwn
    Khan, Mehmood Alam
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Swedish e-Science Research Center, Sweden .
    Quantitative synteny scoring improves homology inference and partitioning of gene families2013In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 14, no Suppl,15, p. S12-Article in journal (Refereed)
    Abstract [en]

    Background

    Clustering sequences into families has long been an important step in characterization of genes and proteins. There are many algorithms developed for this purpose, most of which are based on either direct similarity between gene pairs or some sort of network structure, where weights on edges of constructed graphs are based on similarity. However, conserved synteny is an important signal that can help distinguish homology and it has not been utilized to its fullest potential.

    Results

    Here, we present GenFamClust, a pipeline that combines the network properties of sequence similarity and synteny to assess homology relationship and merge known homologs into groups of gene families. GenFamClust identifies homologs in a more informed and accurate manner as compared to similarity based approaches. We tested our method against the Neighborhood Correlation method on two diverse datasets consisting of fully sequenced genomes of eukaryotes and synthetic data.

    Conclusions

    The results obtained from both datasets confirm that synteny helps determine homology and GenFamClust improves on Neighborhood Correlation method. The accuracy as well as the definition of synteny scores is the most valuable contribution of GenFamClust.

  • 4. Angleby, Helen
    et al.
    Oskarsson, Mattias
    Pang, Junfeng
    Zhang, Ya-ping
    Leitner, Thomas
    Braham, Caitlyn
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab).
    Lundeberg, Joakim
    Webb, Kristen M.
    Savolainen, Peter
    Forensic Informativity of similar to 3000bp of Coding Sequence of Domestic Dog mtDNA2014In: Journal of Forensic Sciences, ISSN 0022-1198, E-ISSN 1556-4029, Vol. 59, no 4, p. 898-908Article in journal (Refereed)
    Abstract [en]

    The discriminatory power of the noncoding control region (CR) of domestic dog mitochondrial DNA alone is relatively low. The extent to which the discriminatory power could be increased by analyzing additional highly variable coding regions of the mitochondrial genome (mtGenome) was therefore investigated. Genetic variability across the mtGenome was evaluated by phylogenetic analysis, and the three most variable similar to 1kb coding regions identified. We then sampled 100 Swedish dogs to represent breeds in accordance with their frequency in the Swedish population. A previously published dataset of 59 dog mtGenomes collected in the United States was also analyzed. Inclusion of the three coding regions increased the exclusion capacity considerably for the Swedish sample, from 0.920 for the CR alone to 0.964 for all four regions. The number of mtDNA types among all 159 dogs increased from 41 to 72, the four most frequent CR haplotypes being resolved into 22 different haplotypes.

  • 5.
    Atle, Andreas
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science(NADA) (together with KTH).
    Approximations of Integral Equations for WaveScattering2006Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Wave scattering is the phenomenon in which a wave field interacts with physical objects. An incoming wave is scattered at the surface of the object and a scattered wave is produced. Common practical cases are acoustic, electromagnetic and elastic wave scattering. The numerical simulation of the scattering process is important, for example, in noise control, antenna design, prediction of radar cross sections and nondestructive testing.

    Important classes of numerical methods for accurate simulation of scattering are based on integral representations of the wave fields and theses representations require the knowledge of potentials on the surfaces of the scattering objects. The potential is typically computed by a numerical approximation of an integral equation that is defined on the surface. We first develop such numerical methods in time domain for the scalar wave equation. The efficiency of the techniques are improved by analytic quadrature and in some cases by local approximation of the potential.

    Most scattering simulations are done for harmonic or single frequency waves. In the electromagnetic case the corresponding integral equation method is called the method of moments. This numerical approximation is computationally very costly for high frequency waves. A simplification is suggested by physical optics, which directly gives an approximation of the potential without the solution of an integral equation. Physical optics is however only accurate for very high frequencies.

    In this thesis we improve the accuracy in the physical optics approximation of scalar waves by basing the computation of the potential on the theory of radiation boundary conditions. This theory describes the local coupling of derivatives in the wave field and if it is applied at the surface of the scattering object it generates an expression for the unknown potential. The full wave field is then computed as for other integral equation methods.

    The new numerical techniques are analyzed mathematically and their efficiency is established in a sequence of numerical experiments. The new on surface radiation conditions give, for example, substantial improvement in the estimation of the scattered waves in the acoustic case. This numerical experiment corresponds to radar cross-section estimation in the electromagnetic case.

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  • 6. Austrin, Per
    et al.
    Manokaran, Rajsekar
    Wenner, Cenny
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). KTH - Royal Institute of Technology, Sweden.
    On the NP-Hardness of Approximating Ordering-Constraint Satisfaction Problems2015In: Theory of Computing, E-ISSN 1557-2862, Vol. 11, article id 10Article in journal (Refereed)
    Abstract [en]

    We show improved NP-hardness of approximating Ordering Constraint Satis-faction Problems (OCSPs). For the two most well-studied OCSPs, Maximum Acyclic Subgraph and Maximum Betweenness, we prove NP-hard approximation factors of 14/15+ε and 1/2+ε. When it is hard to approximate an OCSP by a constant better than takinga uniformly-at-random ordering, then the OCSP is said to be approximation resistant. We show that the Maximum Non-Betweenness Problem is approximation resistant and that there are width-m approximation-resistant OCSPs accepting only a fraction 1/(m/2)! of assignments. These results provide the first examples of approximation-resistant OCSPs only to P != NP.

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  • 7. Benjaminsson, Simon
    et al.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Nexa: A scalable neural simulator with integrated analysis2012In: Network: Computation in Neural Systems, ISSN 0954-898X, Vol. 23, no 4, p. 254-271Article in journal (Refereed)
    Abstract [en]

    Large-scale neural simulations encompass challenges in simulator design, data handling and understanding of simulation output. As the computational power of supercomputers and the size of network models increase, these challenges become even more pronounced. Here we introduce the experimental scalable neural simulator Nexa, for parallel simulation of large-scale neural network models at a high level of biological abstraction and for exploration of the simulation methods involved. It includes firing-rate models and capabilities to build networks using machine learning inspired methods for e.g. self-organization of network architecture and for structural plasticity. We show scalability up to the size of the largest machines currently available for a number of model scenarios. We further demonstrate simulator integration with online analysis and real-time visualization as scalable solutions for the data handling challenges.

  • 8.
    Berthet, Pierre
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Computational Modeling of the Basal Ganglia: Functional Pathways and Reinforcement Learning2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    We perceive the environment via sensor arrays and interact with it through motor outputs. The work of this thesis concerns how the brain selects actions given the information about the perceived state of the world and how it learns and adapts these selections to changes in this environment. Reinforcement learning theories suggest that an action will be more or less likely to be selected if the outcome has been better or worse than expected. A group of subcortical structures, the basal ganglia (BG), is critically involved in both the selection and the reward prediction.

    We developed and investigated a computational model of the BG. We implemented a Bayesian-Hebbian learning rule, which computes the weights between two units based on the probability of their activations. We were able test how various configurations of the represented pathways impacted the performance in several reinforcement learning and conditioning tasks. Then, following the development of a more biologically plausible version with spiking neurons, we simulated lesions in the different pathways and assessed how they affected learning and selection.

    We observed that the evolution of the weights and the performance of the models resembled qualitatively experimental data. The absence of an unique best way to configure the model over all the learning paradigms tested indicates that an agent could dynamically configure its action selection mode, mainly by including or not the reward prediction values in the selection process. We present hypotheses on possible biological substrates for the reward prediction pathway. We base these on the functional requirements for successful learning and on an analysis of the experimental data. We further simulate a loss of dopaminergic neurons similar to that reported in Parkinson’s disease. We suggest that the associated motor symptoms are mostly causedby an impairment of the pathway promoting actions, while the pathway suppressing them seems to remain functional.

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  • 9.
    Berthet, Pierre
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Hellgren-Kotaleski, Jeanette
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Action selection performance of a reconfigurable basal ganglia inspired model with Hebbian-Bayesian Go- NoGo connectivity2012In: Frontiers in Behavioral Neuroscience, E-ISSN 1662-5153, Vol. 6, article id 65Article in journal (Refereed)
    Abstract [en]

    Several studies have shown a strong involvement of the basal ganglia (BG) in action selection and dopamine dependent learning. The dopaminergic signal to striatum, the input stage of the BG, has been commonly described as coding a reward prediction error (RPE), i.e., the difference between the predicted and actual reward. The RPE has been hypothesized to be critical in the modulation of the synaptic plasticity in cortico-striatal synapses in the direct and indirect pathway. We developed an abstract computational model of the BG, with a dual pathway structure functionally corresponding to the direct and indirect pathways, and compared its behavior to biological data as well as other reinforcement learning models. The computations in our model are inspired by Bayesian inference, and the synaptic plasticity changes depend on a three factor Hebbian-Bayesian learning rule based on co-activation of pre- and post-synaptic units and on the value of the RPE. The model builds on a modified Actor-Critic architecture and implements the direct (Go) and the indirect(NoGo) pathway, as well as the reward prediction (RP) system, acting in a complementary fashion. We investigated the performance of the model system when different configurations of the Go, NoGo, and RP system were utilized, e.g., using only the Go, NoGo, or RP system, or combinations of those. Learning performance was investigated in several types of learning paradigms, such as learning-relearning, successive learning, stochastic learning, reversal learning and a two-choice task. The RPE and the activity of the model during learning were similar to monkey electrophysiological and behavioral data. Our results, however, show that there is not a unique best way to configure this BG model to handle well all the learning paradigms tested. We thus suggest that an agent might dynamically configure its action selection mode, possibly depending on task characteristics and also on how much time is available.

  • 10.
    Berthet, Pierre
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Optogenetic Stimulation in a Computational Model of the Basal Ganglia Biases Action Selection and Reward Prediction Error2014In: PLOS ONE, E-ISSN 1932-6203, Vol. 9, no 3, article id e90578Article in journal (Refereed)
    Abstract [en]

    Optogenetic stimulation of specific types of medium spiny neurons (MSNs) in the striatum has been shown to bias the selection of mice in a two choices task. This shift is dependent on the localisation and on the intensity of the stimulation but also on the recent reward history. We have implemented a way to simulate this increased activity produced by the optical flash in our computational model of the basal ganglia (BG). This abstract model features the direct and indirect pathways commonly described in biology, and a reward prediction pathway (RP). The framework is similar to Actor-Critic methods and to the ventral/ dorsal distinction in the striatum. We thus investigated the impact on the selection caused by an added stimulation in each of the three pathways. We were able to reproduce in our model the bias in action selection observed in mice. Our results also showed that biasing the reward prediction is sufficient to create a modification in the action selection. However, we had to increase the percentage of trials with stimulation relative to that in experiments in order to impact the selection. We found that increasing only the reward prediction had a different effect if the stimulation in RP was action dependent (only for a specific action) or not. We further looked at the evolution of the change in the weights depending on the stage of learning within a block. A bias in RP impacts the plasticity differently depending on that stage but also on the outcome. It remains to experimentally test how the dopaminergic neurons are affected by specific stimulations of neurons in the striatum and to relate data to predictions of our model.

  • 11.
    Berthet, Pierre
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Lindahl, Mikael
    Tully, Philip
    Hellgren-Kotaleski, Jeanette
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Functional relevance of different basal ganglia pathways investigated in a spiking model with reward dependent plasticityManuscript (preprint) (Other academic)
  • 12.
    Berthet, Pierre
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Karolinska Institute, Sweden.
    Lindahl, Mikael
    Tully, Philip J.
    Hellgren-Kotaleski, Jeanette
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Karolinska Institute, Sweden.
    Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity2016In: Frontiers in Neural Circuits, E-ISSN 1662-5110, Vol. 10, article id 53Article in journal (Refereed)
    Abstract [en]

    The brain enables animals to behaviorally adapt in order to survive in a complex and dynamic environment, but how reward-oriented behaviors are achieved and computed by its underlying neural circuitry is an open question. To address this concern, we have developed a spiking model of the basal ganglia (BG) that learns to dis-inhibit the action leading to a reward despite ongoing changes in the reward schedule. The architecture of the network features the two pathways commonly described in BG, the direct (denoted D1) and the indirect (denoted D2) pathway, as well as a loop involving striatum and the dopaminergic system. The activity of these dopaminergic neurons conveys the reward prediction error (RPE), which determines the magnitude of synaptic plasticity within the different pathways. All plastic connections implement a versatile four-factor learning rule derived from Bayesian inference that depends upon pre- and post-synaptic activity, receptor type, and dopamine level. Synaptic weight updates occur in the D1 or D2 pathways depending on the sign of the RPE, and an efference copy informs upstream nuclei about the action selected. We demonstrate successful performance of the system in a multiple-choice learning task with a transiently changing reward schedule. We simulate lesioning of the various pathways and show that a condition without the D2 pathway fares worse than one without D1. Additionally, we simulate the degeneration observed in Parkinson's disease (PD) by decreasing the number of dopaminergic neurons during learning. The results suggest that the D1 pathway impairment in PD might have been overlooked. Furthermore, an analysis of the alterations in the synaptic weights shows that using the absolute reward value instead of the RPE leads to a larger change in D1.

  • 13.
    Betsis, Demetre
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    On the numerical construction of optimal designs of regression experiments1985Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A class of efficient methods for the numerical solution of the problem of Optimal Experimental Design is developed and tested on typical examples for D— and A—optimal design. Equivalence theorems are derived by Kuhn-Tucker conditions and the feasible directions approach of Nonlinear Programming. A method for construction of the initial approximation in the case of D—optimal design is proposed and tested. The method yields the exact solution in many cases. Newton’s methods are tested in the D—optimal design case.

  • 14. Brocke, Ekaterina
    et al.
    Bhalla, Upinder S.
    Djurfeldt, Mikael
    Hellgren Kotaleski, Jeanette
    Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). KTH Royal Institute of Technology, Sweden; Karolinska Institute, Sweden.
    Hanke, Michael
    Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations2016In: Frontiers in Computational Neuroscience, E-ISSN 1662-5188, Vol. 10, article id 97Article in journal (Refereed)
    Abstract [en]

    Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience.

  • 15. Bruzelius, Maria
    et al.
    Iglesias, Maria Jesus
    Hong, Mun-Gwan
    Sanchez-Rivera, Laura
    Gyorgy, Beata
    Carlos Souto, Juan
    Frånberg, Mattias
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Karolinska Institutet, Sweden.
    Fredolini, Claudia
    Strawbridge, Rona J.
    Holmström, Margareta
    Hamsten, Anders
    Uhlén, Mathias
    Silveira, Angela
    Manuel Soria, Jose
    Smadja, David M.
    Butler, Lynn M.
    Schwenk, Jochen M.
    Morange, Pierre-Emmanuel
    Tregouet, David-Alexandre
    Odeberg, Jacob
    PDGFB, a new candidate plasma biomarker for venous thromboembolism: results from the VEREMA affinity proteomics study2016In: Blood, ISSN 0006-4971, E-ISSN 1528-0020, Vol. 128, no 23, p. E59-E66Article in journal (Refereed)
    Abstract [en]

    There is a clear clinical need for high-specificity plasma biomarkers for predicting risk of venous thromboembolism (VTE), but thus far, such markers have remained elusive. Utilizing affinity reagents from the Human Protein Atlas project and multiplexed immuoassays, we extensively analyzed plasma samples from 2 individual studies to identify candidate protein markers associated with VTE risk. We screened plasma samples from 88 VTE cases and 85 matched controls, collected as part of the Swedish Venous Thromboembolism Biomarker Study, using suspension bead arrays composed of 755 antibodies targeting 408 candidate proteins. We identified significant associations between VTE occurrence and plasma levels of human immunodeficiency virus type I enhancer binding protein 1 (HIVEP1), von Willebrand factor (VWF), glutathione peroxidase 3 (GPX3), and platelet-derived growth factor beta (PDGFB). For replication, we profiled plasma samples of 580 cases and 589 controls from the French FARIVE study. These results confirmed the association of VWF and PDGFB with VTE after correction for multiple testing, whereas only weak trends were observed for HIVEP1 and GPX3. Although plasma levels of VWF and PDGFB correlated modestly (rho similar to 0.30) with each other, they were independently associated with VTE risk in a joint model in FARIVE (VWF P < .001; PDGFB P = .002). PDGF. was verified as the target of the capture antibody by immunocapture mass spectrometry and sandwich enzyme-linked immunosorbent assay. In conclusion, we demonstrate that high-throughput affinity plasma proteomic profiling is a valuable research strategy to identify potential candidate biomarkers for thrombosis-related disorders, and our study suggests a novel association of PDGFB plasma levels with VTE.

  • 16. de Vries, Paul S.
    et al.
    Sabater-Lleal, Maria
    Chasman, Daniel I.
    Trompet, Stella
    Ahluwalia, Tarunveer S.
    Teumer, Alexander
    Kleber, Marcus E.
    Chen, Ming-Huei
    Wang, Jie Jin
    Attia, John R.
    Marioni, Riccardo E.
    Steri, Maristella
    Weng, Lu-Chen
    Pool, Rene
    Grossmann, Vera
    Brody, Jennifer A.
    Venturini, Cristina
    Tanaka, Toshiko
    Rose, Lynda M.
    Oldmeadow, Christopher
    Mazur, Johanna
    Basu, Saonli
    Frånberg, Mattias
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Karolinska Institutet, Sweden.
    Yang, Qiong
    Ligthart, Symen
    Hottenga, Jouke J.
    Rumley, Ann
    Mulas, Antonella
    de Craen, Anton J. M.
    Grotevendt, Anne
    Taylor, Kent D.
    Delgado, Graciela E.
    Kifley, Annette
    Lopez, Lorna M.
    Berentzen, Tina L.
    Mangino, Massimo
    Bandinelli, Stefania
    Morrison, Alanna C.
    Hamsten, Anders
    Tofler, Geoffrey
    de Maat, Moniek P. M.
    Draisma, Harmen H. M.
    Lowe, Gordon D.
    Zoledziewska, Magdalena
    Sattar, Naveed
    Lackner, Karl J.
    Voelker, Uwe
    McKnight, Barbara
    Huang, Jie
    Holliday, Elizabeth G.
    McEvoy, Mark A.
    Starr, John M.
    Hysi, Pirro G.
    Hernandez, Dena G.
    Guan, Weihua
    Rivadeneira, Fernando
    McArdle, Wendy L.
    Slagboom, P. Eline
    Zeller, Tanja
    Psaty, Bruce M.
    Uitterlinden, Andre G.
    de Geus, Eco J. C.
    Stott, David J.
    Binder, Harald
    Hofman, Albert
    Franco, Oscar H.
    Rotter, Jerome I.
    Ferrucci, Luigi
    Spector, Tim D.
    Deary, Ian J.
    Maerz, Winfried
    Greinacher, Andreas
    Wild, Philipp S.
    Cucca, Francesco
    Boomsma, Dorret I.
    Watkins, Hugh
    Tang, Weihong
    Ridker, Paul M.
    Jukema, Jan W.
    Scott, Rodney J.
    Mitchell, Paul
    Hansen, Torben
    O'Donnell, Christopher J.
    Smith, Nicholas L.
    Strachan, David P.
    Dehghan, Abbas
    Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study2017In: PLOS ONE, E-ISSN 1932-6203, Vol. 12, no 1, article id e0167742Article in journal (Refereed)
    Abstract [en]

    An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5x10(-8) is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5x10(-8)), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

  • 17.
    Dorobantu, Mihai
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Walvelet-based algorithms for fast PDE solvers1995Doctoral thesis, monograph (Other academic)
  • 18.
    Elenius, Måns
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA) (together with KTH).
    Computer Simulations of Simple Liquids with Tetrahedral Local Order: the Supercooled Liquid, Solids and Phase Transitions2009Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The understanding of complex condensed matter systems is an area of intense study. In this thesis, some properties of simple liquids with strong preference for tetrahedral local ordering are explored. These liquids are amenable to supercooling, and give complex crystalline structures on eventual crystallisation. All liquids studied are simple, monatomic and are similar to real metallic liquids.

    The vibrational density of states of a glass created in simulation is calculated. We show a correspondence between the vibrational properties of the crystal and the glass, indicating that the vibrational spectra of crystals can be used to understand the more complex vibrational spectra of the glass of the same substance.

    The dynamics of supercooled liquids is investigated using a previously not implemented comprehensive measure of structural relaxation. This new measure decays more slowly in the deeply supercooled domain than the commonly used measure.

    A new atomic model for octagonal quasicrystals is presented. The model is based on findings from a molecular dynamics simulation that resulted in 45˚ twinned β-Mn. A decoration is derived from the β-Mn unit cell and the unit cell of the intermediate structure found at the twinning interface.

    Extensive simulations are used to explore the phase diagram of a liquid at low densities. The resulting phase diagram shows a spinodal line and a phase coexistence region between a liquid and a crystalline phase ending in a critical point. This contradicts the old conclusion of the Landau theory -- that continuous transitions between liquids and crystals cannot exist

    The same liquid is explored at higher densities. Upon cooling the liquid performs a first order liquid-liquid phase transition. The low temperature liquid is shown to be strong and to have very good glass forming abilities. This result offers new insights into fragile to strong transitions and suggests the possibility of a good metallic glass former.

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  • 19.
    Elenius, Måns
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA) (together with KTH).
    Dzugutov, Mikhail
    Dept. of Materials Science and Engineering, Royal Institute of Technology.
    Evidence for a liquid-solid critical point in a simple monatomic system2009In: Journal of Chemical Physics, ISSN 0021-9606, E-ISSN 1089-7690, Vol. 131, no 104502Article in journal (Refereed)
    Abstract [en]

    It is commonly believed that the transition line  separating a liquid and a solid cannot be interrupted by a  critical point. This opinion is based on the traditional  symmetry argument that an isotropic liquid cannot be  continuously transformed into a crystal with a discrete  rotational and translational symmetry. We present here a  molecular-dynamics simulation of a simple monatomic system  suggesting the existence of a liquid-solid spinodal terminating  at a critical point. We show that, in the critical region, the  isotropic liquid continuously transforms into a phase with a  mesoscopic order similar to that of the smectic liquid  crystals. We argue that the existence of both the spinodal and  the critical point can be explained by the close structural  proximity between the mesophase and the crystal. This indicates  a possibility of finding a similar thermodynamic behaviour in  gelating colloids, liquid crystals and polymers.

  • 20.
    Elenius, Måns
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA) (together with KTH).
    Dzugutov, Mikhail
    KTH, MSE.
    Evidence for compact cooperatively rearranging regions in a supercooled liquid2009In: Journal of Physics: Condensed Matter, ISSN 0953-8984, Vol. 21, no 24, p. 245101-1-245101-5Article in journal (Refereed)
    Abstract [en]

    We examine structural relaxation in a supercooled glass-forming liquid simulated by constant-energy constant-volume (NVE) molecular dynamics. Time correlations of the total kinetic energy fluctuations are used as a comprehensive measure of the system’s approach to the ergodic equilibrium. We find that, under cooling, the total structural relaxation becomes delayed as compared with the decay of the component of the intermediate scattering function corresponding to the main peak of the structure factor. This observation can be explained by collective movements of particles preserving many-body structural  orrelations within compact three-dimensional (3D) cooperatively rearranging regions.

  • 21.
    Elenius, Måns
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Oppelstrup, Tomas
    KTH, Numerisk analys och datalogi (NADA), (tills m SU), Numerical Analysis and Computer Science (NADA) (together with SU).
    Dzugutov, Mikhail
    KTH, institutionen för materialvetenskap.
    A polyamorphous fragile to strong transition under equilibrium cooling in a simple monatomic liquidManuscript (preprint) (Other academic)
    Abstract [en]

    Glass transition remains one of the deepest and most interesting  problems of condensed-matter physics. One fundamental aspect of the problem is how to avoid  crystalline nucleation when cooling a liquid towards the glass  transition at an arbitrarily slow rate. The prototype ``ideal glass  formers'' are silica and other inorganic network-forming systems. No  monatomic glass has been obtained so far by cooling from melt.  Whether a monatomic system can reproduce the behavior of  silica-like glass formers is a question of great interest, both  conceptual and for technological applications. We present a  molecular-dynamics simulation of a simple monatomic system based on  a metallic-like pair potential. We demonstrate that, while remaining  stable with respect to crystallization, the system performs under  cooling a first order phase transition from a fragile to an  extremely strong liquid state. The low-temperature  liquid phase can be cooled to a state of very high viscosity and low  diffusivity while remaining in equilibrium. This result may provide  a significant insight into the formation mechanisms of metallic  glasses.

  • 22.
    Elenius, Måns
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA) (together with KTH).
    Zetterling, Fredrik
    Dzugutov, Mikhail
    KTH, MSE.
    Fredrickson, Daniel
    Department of Chemistry, University of Wisconsin.
    Lidin, Sven
    Stockholm University, Faculty of Science, Department of Physical, Inorganic and Structural Chemistry, Department of Inorganic Chemistry.
    Structural model for octagonal quasicrystals derived from octagonal symmetry elements arising in beta-Mn crystallization of a simple monatomic liquid2009In: Physical Review B Condensed Matter, ISSN 0163-1829, E-ISSN 1095-3795, Vol. 79, no 14, p. 144201-1-144201-10Article in journal (Refereed)
    Abstract [en]

    While performing molecular-dynamics simulations of a simple monatomic liquid, we observed the crystallization of a material displaying octagonal symmetry in its simulated diffraction pattern. Inspection of the atomic arrangements in the crystallization product reveals large grains of the beta-Mn structure aligned along a common fourfold axis, with 45° rotations between neighboring grains. These 45° rotations can be traced to the intercession of a second crystalline structure fused epitaxially to the beta-Mn domain surfaces, whose primitive cell has lattice parameters a=b=c=a_{beta-Mn}, alpha =beta =90°, and gamma =45°. This secondary phase adopts a structure which appears to have no known counterpart in the experimental literature, but can be simply derived from the Cr3Si and Al3Zr4 structure types. We used these observations as the basis for an atomistic structural model for octagonal quasicrystals, in which the beta-Mn and the secondary phase structure unit cells serve as square and rhombic tiles (in projection), respectively. Its diffraction pattern down the octagonal axis resembles those experimentally measured. The model is unique in being consistent with high-resolution electron microscopy images showing square and rhombic units with edge-lengths equal to that of the beta-Mn unit cell. Energy minimization of this configuration, using the same pair potential as above, results in an alternative octagonal quasiperiodic structure with the same tiling but a different atomic decoration and diffraction pattern.

  • 23. Emanuelsson, Olof
    et al.
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Swedish e-Science Research Center, Sweden.
    Käll, Lukas
    Engagera och aktivera studenter med inspiration från konferenser: examination genom poster-presentation2014In: Proceedings 2014: 8:e Pedagogiska inspirationskonferensen 17 december 2014, Lund: Lund University , 2014Conference paper (Refereed)
    Abstract [sv]

    I en forskningsnära kurs om 7.5 hp på master-nivå inom bioinformatikämnet vid KTH består drygt halva kursen av ett projekt som genomförs i grupper om tre studenter. Varje projekt har en egen projektuppgift med inget eller marginellt överlapp med andra gruppers uppgifter. Projekten är så gott som uteslutande baserade på aktuella frågeställningar i lärarteamets egna forskningsgrupper eller deras närhet. Projektet redovisas dels genom en posterpresentation, dels med individuell webbaserad projektdagbok. Vid posterredovisningen, som omfattar tre timmar i slutet av tentamensperioden, är alla kursdeltagare med. Vi försöker i möjligaste mån efterlikna situationen där ett autentiskt forskningsresultat presenteras på en riktig konferens. Varje deltagare (student) förväntas alltså ta del av varje annan grupps poster, på samma sätt som sker vid de flesta vetenskapliga konferenser. Vi genomför en enklare kamratbedömning på posternivå, där varje student ska avge en kort och konfidentiell kommentar om var och en av övriga postrar. Kursens lärare bedömer förstås också postrarna. En av svårigheterna är att sätta individuella betyg. Här använder vi oss av individuella projektdagböcker, som ger vägledning till de olika individernas insatser inom projektet. Vi har provat detta under fyra kursomgångar med som mest sju projekt. Examinationsformen är rolig och motiverande både för studenterna och lärarna.

  • 24. Eriksson, Johan
    et al.
    Vogel, Edward K.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). KTH Royal Institute of Technology, Sweden.
    Bergström, Fredrik
    Nyberg, Lars
    Neurocognitive Architecture of Working Memory2015In: Neuron, ISSN 0896-6273, E-ISSN 1097-4199, Vol. 88, no 1, p. 33-46Article, review/survey (Refereed)
    Abstract [en]

    A crucial role for working memory in temporary information processing and guidance of complex behavior has been recognized for many decades. There is emerging consensus that working-memory maintenance results from the interactions among long-term memory representations and basic processes, including attention, that are instantiated as reentrant loops between frontal and posterior cortical areas, as well as sub-cortical structures. The nature of such interactions can account for capacity limitations, lifespan changes, and restricted transfer after working-memory training. Recent data and models indicate that working memory may also be based on synaptic plasticity and that working memory can operate on non-consciously perceived information.

  • 25.
    Eriksson, Olivia
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). KTH Royal Institute of Technology, Sweden; Swedish e-Science Research Centre (SeRC), Sweden.
    Jauhiainen, Alexandra
    Sasane, Sara Maad
    Kramer, Andrei
    Nair, Anu G.
    Sartorius, Carolina
    Hellgren Kotaleski, Jeanette
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). KTH Royal Institute of Technology, Sweden; Swedish e-Science Research Centre (SeRC), Sweden.
    Uncertainty quantification, propagation and characterization by Bayesian analysis combined with global sensitivity analysis applied to dynamical intracellular pathway models2019In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 35, no 2, p. 284-292Article in journal (Refereed)
    Abstract [en]

    Motivation: Dynamical models describing intracellular phenomena are increasing in size and complexity as more information is obtained from experiments. These models are often over-parameterized with respect to the quantitative data used for parameter estimation, resulting in uncertainty in the individual parameter estimates as well as in the predictions made from the model. Here we combine Bayesian analysis with global sensitivity analysis (GSA) in order to give better informed predictions; to point out weaker parts of the model that are important targets for further experiments, as well as to give guidance on parameters that are essential in distinguishing different qualitative output behaviours.

    Results: We used approximate Bayesian computation (ABC) to estimate the model parameters from experimental data, as well as to quantify the uncertainty in this estimation (inverse uncertainty quantification), resulting in a posterior distribution for the parameters. This parameter uncertainty was next propagated to a corresponding uncertainty in the predictions (forward uncertainty propagation), and a GSA was performed on the predictions using the posterior distribution as the possible values for the parameters. This methodology was applied on a relatively large model relevant for synaptic plasticity, using experimental data from several sources. We could hereby point out those parameters that by themselves have the largest contribution to the uncertainty of the prediction as well as identify parameters important to separate between qualitatively different predictions. This approach is useful both for experimental design as well as model building.

  • 26.
    Ersmark, Erik
    et al.
    Stockholm University, Faculty of Science, Department of Zoology. Swedish Museum of Natural History, Sweden.
    Klütsch, Cornelya
    Chan, Yvonne
    Dalén, Love
    Stockholm University, Faculty of Science, Department of Zoology.
    Sinding-Larsen, Mikkel
    Gilbert, Thomas
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Fain, Steven R.
    Illarionova, Natalia
    Oskarsson, Mattias
    Uhlén, Mathias
    Zhang, Ya-Ping
    Savolainen, Peter
    From the past to the present: Wolf phylogeography and demographic history based on the mitochondrial control regionManuscript (preprint) (Other academic)
  • 27. Fiebig, Florian
    et al.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation2017In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 37, no 1, p. 83-96Article in journal (Refereed)
    Abstract [en]

    A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism.

  • 28. Fiebig, Florian
    et al.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Memory consolidation from seconds to weeks: a three-stage neural network model with autonomous reinstatement dynamics2014In: Frontiers in Computational Neuroscience, E-ISSN 1662-5188, Vol. 8, p. 64-Article in journal (Refereed)
    Abstract [en]

    Declarative long-term memories are not created in an instant. Gradual stabilization and temporally shifting dependence of acquired declarative memories in different brain regions called systems consolidation- can be tracked in time by lesion experiments. The observation of temporally graded retrograde amnesia(RA) following hippocampal lesions points to a gradual transfer of memory from hippocampus to neocortical long-term memory. Spontaneous reactivations of hippocampal memories, asobserved in place cell reactivations during slow wave- sleep, are supposed to driven eocortical reinstatements and facilitate this process. We proposea functional neural network implementation of these ideas and further more suggest anextended three-state framework that includes the prefrontal cortex( PFC). It bridges the temporal chasm between working memory percepts on the scale of seconds and consolidated long-term memory on the scale of weeks or months. Wes how that our three-stage model can autonomously produce the necessary stochastic reactivation dynamics for successful episodic memory consolidation. There sulting learning system is shown to exhibit classical memory effects seen in experimental studies, such as retrograde and anterograde amnesia(AA) after simulated hippocampal lesioning; further more the model reproduces peculiar biological findings on memory modulation, such as retrograde facilitation of memory after suppressed acquisition of new longterm memories- similar to the effects of benzodiazepines on memory.

  • 29. Fried, Dror
    et al.
    Shimony, Solomon Eyal
    Benbassat, Amit
    Wenner, Cenny
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). KTH Royal Inst Technol, SE-10044 Stockholm, Sweden.
    Complexity of Canadian traveler problem variants2013In: Theoretical Computer Science, ISSN 0304-3975, E-ISSN 1879-2294, Vol. 487, p. 1-16Article in journal (Refereed)
    Abstract [en]

    The Canadian traveler problem (CTP) is the problem of traversing a given graph, where some of the edges may be blocked a state which is revealed only upon reaching an incident vertex. Originally stated by Papadimitriou and Yannakakis (1991) [1], the adversarial version of the CTP was shown to be PSPACE-complete, with the stochastic version shown to be in PSPACE and #P-hard. We show that the stochastic CTP is also PSPACE-complete: initially proving PSPACE-hardness for the dependent version of the stochastic CTP, and proceeding with gadgets that allow us to extend the proof to the independent case. Since for disjoint-path graphs, the CTP can be solved in polynomial time, we examine the complexity of the more general remote-sensing CTP, and show that it is NP-hard even for disjoint-path graphs.

  • 30.
    Frånberg, Mattias
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Karolinska Institutet, Sweden.
    Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders2018In: American Journal of Human Genetics, ISSN 0002-9297, E-ISSN 1537-6605, Vol. 103, no 5, p. 691-706Article in journal (Refereed)
    Abstract [en]

    C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 x 10(-8)). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

  • 31.
    Frånberg, Mattias
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Karolinska Institutet, Sweden; Karolinska Universitetsjukhuset, Sweden.
    Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk2017In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 49, no 3, p. 403-415Article in journal (Refereed)
    Abstract [en]

    Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.

  • 32.
    Frånberg, Mattias
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Karolinska Institutet, Sweden.
    Gertow, Karl
    Hamsten, Anders
    Lagergren, Jens
    Sennblad, Bengt
    Discovering Genetic Interactions in Large-Scale Association Studies by Stage-wise Likelihood Ratio Tests2015In: PLOS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 11, no 9, article id e1005502Article in journal (Refereed)
    Abstract [en]

    Despite the success of genome-wide association studies in medical genetics, the underlying genetics of many complex diseases remains enigmatic. One plausible reason for this could be the failure to account for the presence of genetic interactions in current analyses. Exhaustive investigations of interactions are typically infeasible because the vast number of possible interactions impose hard statistical and computational challenges. There is, therefore, a need for computationally efficient methods that build on models appropriately capturing interaction. We introduce a new methodology where we augment the interaction hypothesis with a set of simpler hypotheses that are tested, in order of their complexity, against a saturated alternative hypothesis representing interaction. This sequential testing provides an efficient way to reduce the number of non-interacting variant pairs before the final interaction test. We devise two different methods, one that relies on a priori estimated numbers of marginally associated variants to correct for multiple tests, and a second that does this adaptively. We show that our methodology in general has an improved statistical power in comparison to seven other methods, and, using the idea of closed testing, that it controls the family-wise error rate. We apply our methodology to genetic data from the PRO-CARDIS coronary artery disease case/control cohort and discover three distinct interactions. While analyses on simulated data suggest that the statistical power may suffice for an exhaustive search of all variant pairs in ideal cases, we explore strategies for a priori selecting subsets of variant pairs to test. Our new methodology facilitates identification of new disease-relevant interactions from existing and future genome-wide association data, which may involve genes with previously unknown association to the disease. Moreover, it enables construction of interaction networks that provide a systems biology view of complex diseases, serving as a basis for more comprehensive understanding of disease pathophysiology and its clinical consequences.

  • 33.
    Frånberg, Mattias
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Karolinska Institutet, Sweden.
    Strawbridge, Rona J.
    Hamster, Anders
    de Faire, Ulf
    Lagergren, Jens
    Sennblad, Bengt
    Fast and general tests of genetic interaction for genome-wide association studies2017In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 13, no 6, article id e1005556Article in journal (Refereed)
    Abstract [en]

    A complex disease has, by definition, multiple genetic causes. In theory, these causes could be identified individually, but their identification will likely benefit from informed use of anticipated interactions between causes. In addition, characterizing and understanding interactions must be considered key to revealing the etiology of any complex disease. Large-scale collaborative efforts are now paving the way for comprehensive studies of interaction. As a consequence, there is a need for methods with a computational efficiency sufficient for modern data sets as well as for improvements of statistical accuracy and power. Another issue is that, currently, the relation between different methods for interaction inference is in many cases not transparent, complicating the comparison and interpretation of results between different interaction studies. In this paper we present computationally efficient tests of interaction for the complete family of generalized linear models (GLMs). The tests can be applied for inference of single or multiple interaction parameters, but we show, by simulation, that jointly testing the full set of interaction parameters yields superior power and control of false positive rate. Based on these tests we also describe how to combine results from multiple independent studies of interaction in a meta-analysis. We investigate the impact of several assumptions commonly made when modeling interactions. We also show that, across the important class of models with a full set of interaction parameters, jointly testing the interaction parameters yields identical results. Further, we apply our method to genetic data for cardiovascular disease. This allowed us to identify a putative interaction involved in Lp(a) plasma levels between two 'tag' variants in the LPA locus (p = 2.42 . 10(-09)) as well as replicate the interaction (p = 6.97 . 10(-07)). Finally, our meta-analysis method is used in a small (N = 16,181) study of interactions in myocardial infarction.

  • 34. Gaulton, Kyle J.
    et al.
    Ferreira, Teresa
    Lee, Yeji
    Raimondo, Anne
    Maegi, Reedik
    Reschen, Michael E.
    Mahajan, Anubha
    Locke, Adam
    Rayner, N. William
    Robertson, Neil
    Scott, Robert A.
    Prokopenko, Inga
    Scott, Laura J.
    Green, Todd
    Sparso, Thomas
    Thuillier, Dorothee
    Yengo, Loic
    Grallert, Harald
    Wahl, Simone
    Frånberg, Mattias
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Karolinska Institutet, Sweden.
    Strawbridge, Rona J.
    Kestler, Hans
    Chheda, Himanshu
    Eisele, Lewin
    Gustafsson, Stefan
    Steinthorsdottir, Valgerdur
    Thorleifsson, Gudmar
    Qi, Lu
    Karssen, Lennart C.
    van Leeuwen, Elisabeth M.
    Willems, Sara M.
    Li, Man
    Chen, Han
    Fuchsberger, Christian
    Kwan, Phoenix
    Ma, Clement
    Linderman, Michael
    Lu, Yingchang
    Thomsen, Soren K.
    Rundle, Jana K.
    Beer, Nicola L.
    van de Bunt, Martijn
    Chalisey, Anil
    Kang, Hyun Min
    Voight, Benjamin F.
    Abecasis, Goncalo R.
    Almgren, Peter
    Baldassarre, Damiano
    Balkau, Beverley
    Benediktsson, Rafn
    Blueher, Matthias
    Boeing, Heiner
    Bonnycastle, Lori L.
    Bottinger, Erwin P.
    Burtt, Noel P.
    Carey, Jason
    Charpentier, Guillaume
    Chines, Peter S.
    Cornelis, Marilyn C.
    Couper, David J.
    Crenshaw, Andrew T.
    van Dam, Rob M.
    Doney, Alex S. F.
    Dorkhan, Mozhgan
    Edkins, Sarah
    Eriksson, Johan G.
    Esko, Tonu
    Eury, Elodie
    Fadista, Joao
    Flannick, Jason
    Fontanillas, Pierre
    Fox, Caroline
    Franks, Paul W.
    Gertow, Karl
    Gieger, Christian
    Gigante, Bruna
    Gottesman, Omri
    Grant, George B.
    Grarup, Niels
    Groves, Christopher J.
    Hassinen, Maija
    Have, Christian T.
    Herder, Christian
    Holmen, Oddgeir L.
    Hreidarsson, Astradur B.
    Humphries, Steve E.
    Hunter, David J.
    Jackson, Anne U.
    Jonsson, Anna
    Jorgensen, Marit E.
    Jorgensen, Torben
    Kao, Wen-Hong L.
    Kerrison, Nicola D.
    Kinnunen, Leena
    Klopp, Norman
    Kong, Augustine
    Kovacs, Peter
    Kraft, Peter
    Kravic, Jasmina
    Langford, Cordelia
    Leander, Karin
    Liang, Liming
    Lichtner, Peter
    Lindgren, Cecilia M.
    Lindholm, Eero
    Linneberg, Allan
    Liu, Ching-Ti
    Lobbens, Stephane
    Luan, Jian'an
    Lyssenko, Valeriya
    Mannisto, Satu
    McLeod, Olga
    Meyer, Julia
    Mihailov, Evelin
    Mirza, Ghazala
    Muehleisen, Thomas W.
    Mueller-Nurasyid, Martina
    Navarro, Carmen
    Noethen, Markus M.
    Oskolkov, Nikolay N.
    Owen, Katharine R.
    Palli, Domenico
    Pechlivanis, Sonali
    Peltonen, Leena
    Perry, John R. B.
    Platou, Carl G. P.
    Roden, Michael
    Ruderfer, Douglas
    Rybin, Denis
    van der Schouw, Yvonne T.
    Sennblad, Bengt
    Sigurdsson, Gunnar
    Stancakova, Alena
    Steinbach, Gerald
    Storm, Petter
    Strauch, Konstantin
    Stringham, Heather M.
    Sun, Qi
    Thorand, Barbara
    Tikkanen, Emmi
    Tonjes, Anke
    Trakalo, Joseph
    Tremoli, Elena
    Tuomi, Tiinamaija
    Wennauer, Roman
    Wiltshire, Steven
    Wood, Andrew R.
    Zeggini, Eleftheria
    Dunham, Ian
    Birney, Ewan
    Pasquali, Lorenzo
    Ferrer, Jorge
    Loos, Ruth J. F.
    Dupuis, Josee
    Florez, Jose C.
    Boerwinkle, Eric
    Pankow, James S.
    van Duijn, Cornelia
    Sijbrands, Eric
    Meigs, James B.
    Hu, Frank B.
    Thorsteinsdottir, Unnur
    Stefansson, Kari
    Lakka, Timo A.
    Rauramaa, Rainer
    Stumvoll, Michael
    Pedersen, Nancy L.
    Lind, Lars
    Keinanen-Kiukaanniemi, Sirkka M.
    Korpi-Hyovalti, Eeva
    Saaristo, Timo E.
    Saltevo, Juha
    Kuusisto, Johanna
    Laakso, Markku
    Metspalu, Andres
    Erbel, Raimund
    Joecke, Karl-Heinz
    Moebus, Susanne
    Ripatti, Samuli
    Salomaa, Veikko
    Ingelsson, Erik
    Boehm, Bernhard O.
    Bergman, Richard N.
    Collins, Francis S.
    Mohlke, Karen L.
    Koistinen, Heikki
    Tuomilehto, Jaakko
    Hveem, Kristian
    Njolstad, Inger
    Deloukas, Panagiotis
    Donnelly, Peter J.
    Frayling, Timothy M.
    Hattersley, Andrew T.
    de Faire, Ulf
    Hamsten, Anders
    Illig, Thomas
    Peters, Annette
    Cauchi, Stephane
    Sladek, Rob
    Froguel, Philippe
    Hansen, Torben
    Pedersen, Oluf
    Morris, Andrew D.
    Palmer, Collin N. A.
    Kathiresan, Sekar
    Melander, Olle
    Nilsson, Peter M.
    Groop, Leif C.
    Barroso, Ines
    Langenberg, Claudia
    Wareham, Nicholas J.
    O'Callaghan, Christopher A.
    Gloyn, Anna L.
    Altshuler, David
    Boehnke, Michael
    Teslovich, Tanya M.
    McCarthy, Mark I.
    Morris, Andrew P.
    Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci2015In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 47, no 12, p. 1415-+Article in journal (Refereed)
    Abstract [en]

    We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

  • 35.
    Glimming, Johan
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science(NADA) (together with KTH).
    Computational Soundness and Adequacy for Typed Object Calculus2008In: International Workshop on Foundations of Object-Oriented Languages (FOOL 2008, co-located with POPL 2008), ACM SIGPLAN, Vol. Jan.Article in journal (Refereed)
  • 36.
    Glimming, Johan
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science(NADA) (together with KTH).
    Parametric (Co)Iteration vs. Primitive Direcursion2007In: Algebra and Coalgebra in Computer Science: Second International Conference, CALCO 2007, Bergen, Norway, August 20-24, 2007. Proceedings, 2007, p. 257-278Chapter in book (Other academic)
  • 37.
    Glimming, Johan
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science(NADA) (together with KTH).
    Primitive Direcursion and Difunctorial Semantics of Typed Object Calculus2007Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In the first part of this thesis, we contribute to the semantics of typed object calculus by giving (a) a category-theoretic denotational semantics using partial maps making use of an algebraic compactness assumption, (b) a notion of "wrappers'' by which algebraic datatypes can be represented as object types, and (c) proofs of computational soundness and adequacy of typed object calculus via Plotkin's FPC (with lazy operational semantics), thus making models of FPC suitable also for first-order typed object calculus (with recursive objects supporting method update, but not subtyping). It follows that a valid equation in the model induces operationally congruent terms in the language, so that program algebras can be studied. For (c), we also develop an extended first-order typed object calculus, and prove subject reduction. The second part of the thesis concerns recursion principles on datatypes including the untyped lambda calculus as a special case. Freyd showed that in certain domain theoretic categories, locally continuous functors have minimal invariants, which possess a structure that he termed dialgebra. This gives rise to a category of dialgebras and homomorphisms, where the minimal invariants are initial, inducing a powerful recursion scheme (direcursion) on a complete partial order. We identify a problem that appears when we translate (co)iterative functions to direcursion, and as a solution to this problem we develop a recursion scheme (primitive direcursion). This immediately gives a number of examples of direcursive functions, improving on the situation in the literature where only a few examples have appeared. By means of a case study, this line of work is connected to object calculus models.

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  • 38.
    Glimming, Johan
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Ghani, Neil
    Difunctorial Semantics of Object Calculus2005In: Electronic Notes in Theoretical Computer Science, E-ISSN 1571-0661, Vol. 138, no 2, p. 79-94Article in journal (Refereed)
  • 39. Gutierrez-Arenas, Omar
    et al.
    Eriksson, Olivia
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Hellgren Kotaleski, Jeanette
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden; Karolinska Institutet, Sweden.
    Segregation and Crosstalk of D1 Receptor-Mediated Activation of ERK in Striatal Medium Spiny Neurons upon Acute Administration of Psychostimulants2014In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 10, no 1, p. e1003445-Article in journal (Refereed)
    Abstract [en]

    The convergence of corticostriatal glutamate and dopamine from the midbrain in the striatal medium spiny neurons (MSN) triggers synaptic plasticity that underlies reinforcement learning and pathological conditions such as psychostimulant addiction. The increase in striatal dopamine produced by the acute administration of psychostimulants has been found to activate not only effectors of the AC5/cAMP/PKA signaling cascade such as GluR1, but also effectors of the NMDAR/Ca2+/RAS cascade such as ERK. The dopamine-triggered effects on both these cascades are mediated by D1R coupled to Golf but while the phosphorylation of GluR1 is affected by reductions in the available amount of Golf but not of D1R, the activation of ERK follows the opposite pattern. This segregation is puzzling considering that D1R-induced Golf activation monotonically increases with DA and that there is crosstalk from the AC5/cAMP/PKA cascade to the NMDAR/Ca2+/RAS cascade via a STEP (a tyrosine phosphatase). In this work, we developed a signaling model which accounts for this segregation based on the assumption that a common pool of D1R and Golf is distributed in two D1R/Golf signaling compartments. This model integrates a relatively large amount of experimental data for neurons in vivo and in vitro. We used it to explore the crosstalk topologies under which the sensitivities of the AC5/cAMP/PKA signaling cascade to reductions in D1R or Golf are transferred or not to the activation of ERK. We found that the sequestration of STEP by its substrate ERK together with the insensitivity of STEP activity on targets upstream of ERK (i.e. Fyn and NR2B) to PKA phosphorylation are able to explain the experimentally observed segregation. This model provides a quantitative framework for simulation based experiments to study signaling required for long term potentiation in MSNs.

  • 40.
    Hagdahl, Stefan
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science(NADA) (together with KTH).
    Hybrid Methods for Computational Electromagnetics in Frequency Domain2005Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In this thesis we study hybrid numerical methods to be used in computational electromagnetics. The purpose is to address a wide frequency range relative to a given geometry. We also focus on efficient and robust numerical algorithms for computing the so called Smooth Surface Diffraction predicted by Geometrical Theory of Diffraction (GTD). We restrict the presentation to frequency domain scattering problems.

    The hybrid methods consist in combinations of Boundary Element Methods and asymptotic methods. Three hybrids will be presented. One of them has been developed from a theoretical idea to an industrial code. The two other hybrids will be presented mainly from a theoretical perspective.

    To be able to compute the Smooth Surface Diffracted field we introduce a numerical method that is to be used with surface curvature sensitive meshing, complemented with auxiliary data taken from a geometry database. By using two geometry representations we can show first order convergence and we then achieve an efficient and robust numerical algorithm. This numerical algorithm may be an essential part of an GTD implementation which in its turn is a component in the hybrid methods.

    As a background to our new techiniques we will also give short introductions to the Boundary Element Method and the Geometrical Theory of Diffraction from a theoretical and implementational point of view.

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  • 41.
    He, Yiyang
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    A Physically Based Pipeline for Real-Time Simulation and Rendering of Realistic Fire and Smoke2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    With the rapidly growing computational power of modern computers, physically based rendering has found its way into real world applications. Real-time simulations and renderings of fire and smoke had become one major research interest in modern video game industry, and will continue being one important research direction in computer graphics.

    To visually recreate realistic dynamic fire and smoke is a complicated problem. Furthermore, to solve the problem requires knowledge from various areas, ranged from computer graphics and image processing to computational physics and chemistry. Even though most of the areas are well-studied separately, when combined, new challenges will emerge. This thesis focuses on three aspects of the problem, dynamic, real-time and realism, to propose a solution in form of a GPGPU pipeline, along with its implementation. Three main areas with application in the problem are discussed in detail: fluid simulation, volumetric radiance estimation and volumetric rendering. The weights are laid upon the first two areas. The results are evaluated around the three aspects, with graphical demonstrations and performance measurements.

    Uniform grids are used with Finite Difference (FD) discretization scheme to simplify the computation. FD schemes are easy to implement in parallel, especially with ComputeShader, which is well supported in Unity engine. The whole implementation can easily be integrated into any real-world applications in Unity or other game engines that support DirectX 11 or higher.

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    nuke
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    thick_smoke
    Download (zip)
    demo_dx12_gpu
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    color_reproduction
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    eval
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    fire_glow
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    fire_temperature
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    pipeline
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    various
  • 42.
    Herman, Pawel Andrzej
    et al.
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Lundqvist, Mikael
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Nested theta to gamma oscillations and precise spatiotemporal firing during memory retrieval in a simulated attractor network2013In: Brain Research, ISSN 0006-8993, E-ISSN 1872-6240, Vol. 1536, no S1, p. 68-87Article in journal (Refereed)
    Abstract [en]

    Nested oscillations, where the phase of the underlying slow rhythm modulates the power of faster oscillations, have recently attracted considerable research attention as the increased phase-coupling of cross-frequency oscillations has been shown to relate to memory processes. Here we investigate the hypothesis that reactivations of memory patterns, induced by either external stimuli or internal dynamics, are manifested as distributed cell assemblies oscillating at gamma-like frequencies with life-times on a theta scale. For this purpose, we study the spatiotemporal oscillatory dynamics of a previously developed meso-scale attractor network model as a correlate of its memory function. The focus is on a hierarchical nested organization of neural oscillations in delta/theta (2–5 Hz) and gamma frequency bands (25–35 Hz), and in some conditions even in lower alpha band (8–12 Hz), which emerge in the synthesized field potentials during attractor memory retrieval. We also examine spiking behavior of the network in close relation to oscillations. Despite highly irregular firing during memory retrieval and random connectivity within each cell assembly, we observe precise spatiotemporal firing patterns that repeat across memory activations at a rate higher than expected from random firing. In contrast to earlier studies aimed at modeling neural oscillations, our attractor memory network allows us to elaborate on the functional context of emerging rhythms and discuss their relevance. We provide support for the hypothesis that the dynamics of coherent delta/theta oscillations constitute an important aspect of the formation and replay of neuronal assemblies.

  • 43.
    Holst, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    The Use of a Bayesian Neural Network Model for Classification Tasks.1997Doctoral thesis, monograph (Other academic)
  • 44.
    Johansson, Christer
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science(NADA) (together with KTH).
    Numerical methods for waveguide modelling2006Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Waveguides are used to transmit electromagnetic signals. Their geometry is typically long and slender. This particular shape can be used in the design of efficient computational methods. Only special modes are transmitted and eigenvalue and eigenvector analysis becomes important.

    We develop finite-element systems for solving electromagnetic field problems in time and frequency domain for closed waveguide cross-sections filled with various materials. The frequency domain discretization of the cross-section for the waveguide produces an algebraic eigenvalue problem. A general program based on Arnoldi's method and ARPACK has been written using node and edge elements to approximate the field. A serious problem with standard node elements is the occurrence of spurious solutions due to improper modeling of the null space of the curl operator. Edge elements remove such non physical spurious solutions.

    Numerical examples are given for homogeneous and inhomogeneous waveguides. The homogeneous results are compared to analytical solutions to demonstrate that the right order of convergence is achieved.

    Computations on more complicated inhomogeneous waveguides with and without striplines, are compared to results found in the literature together with grid convergence studies. We also give examples where corner singularities are addressed with $hp$-adaptive methods.

    The code is used in an industrial environment, together with 3-D time and frequency domain solvers for Maxwell's equations on general domains. For the full 3-D time domain simulations, cross section simulations are used as input on an artificial boundary that we define as a waveguide port. The excitation is done by a Huygens' surface and the backscattered field is taken care of by an unsplit perfectly matched layer. The results have been compared to what analytical input would give.

  • 45.
    Kahles, André
    et al.
    Kungliga Tekniska Högskolan.
    Sarqume, Fahad
    Kungliga Tekniska Högskolan.
    Savolainen, Peter
    Kungliga Tekniska Högskolan.
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Kungliga Tekniska Högskolan.
    Excap: maximization of haplotypic diversity of linked markers.2013In: PLOS ONE, E-ISSN 1932-6203, Vol. 8, no 11, p. e79012-Article in journal (Refereed)
    Abstract [en]

    Genetic markers, defined as variable regions of DNA, can be utilized for distinguishing individuals or populations. As long as markers are independent, it is easy to combine the information they provide. For nonrecombinant sequences like mtDNA, choosing the right set of markers for forensic applications can be difficult and requires careful consideration. In particular, one wants to maximize the utility of the markers. Until now, this has mainly been done by hand. We propose an algorithm that finds the most informative subset of a set of markers. The algorithm uses a depth first search combined with a branch-and-bound approach. Since the worst case complexity is exponential, we also propose some data-reduction techniques and a heuristic. We implemented the algorithm and applied it to two forensic caseworks using mitochondrial DNA, which resulted in marker sets with significantly improved haplotypic diversity compared to previous suggestions. Additionally, we evaluated the quality of the estimation with an artificial dataset of mtDNA. The heuristic is shown to provide extensive speedup at little cost in accuracy.

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  • 46. Kaplan, Bernhard A.
    et al.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system2014In: Frontiers in Neural Circuits, E-ISSN 1662-5110, Vol. 8, p. 5-Article in journal (Refereed)
    Abstract [en]

    Olfactory sensory information passes through several processing stages before an odor percept emerges. The question how the olfactory system learns to create odor representations linking those different levels and how it learns to connect and discriminate between them is largely unresolved. We present a large-scale network model with single and multi-compartmental Hodgkin-Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. The properties of ORNs were tuned to show saturated response curves with increasing concentration as seen in experiments. On the level of the OB we explored the possibility of using a fuzzy concentration interval code, which was implemented through dendro-dendritic inhibition leading to winner-take-all like dynamics between mitral/tufted cells belonging to the same glomerulus. The connectivity from mitral/tufted cells to PC neurons was self-organized from a mutual information measure and by using a competitive Hebbian-Bayesian learning algorithm based on the response patterns of mitral/tufted cells to different odors yielding a distributed feed-forward projection to the PC. The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian-Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures.

  • 47. Kaplan, Bernhard A.
    et al.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden.
    Masson, Guillaume S.
    Perrinet, Laurent U.
    Anisotropic connectivity implements motion-based prediction in a spiking neural network2013In: Frontiers in Computational Neuroscience, E-ISSN 1662-5188, Vol. 7, p. UNSP 112-Article in journal (Refereed)
    Abstract [en]

    Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. We present a network model of conductance-based integrate-and-fire neurons inspired by the architecture of retinotopic cortical areas that assumes predictive coding is implemented through network connectivity, namely in the connection delays and in selectiveness for the tuning properties of source and target cells. We show that the applied connection pattern leads to motion-based prediction in an experiment tracking a moving dot. In contrast to our proposed model, a network with random or isotropic connectivity fails to predict the path when the moving dot disappears. Furthermore, we show that a simple linear decoding approach is sufficient to transform neuronal spiking activity into a probabilistic estimate for reading out the target trajectory.

  • 48. Khan, Mehmood Alam
    et al.
    Elias, Isaac
    Sjölund, Erik
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Nylander, Kristina
    Guimera, Roman Valls
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Schobesberger, Richard
    Schmitzberger, Peter
    Lagergren, Jens
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA).
    Fastphylo: Fast tools for phylogenetics2013In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 14, p. 334-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Distance methods are ubiquitous tools in phylogenetics.Their primary purpose may be to reconstructevolutionary history, but they are also used as components in bioinformatic pipelines. However, poorcomputational efficiency has been a constraint on the applicability of distance methods on very largeproblem instances.

    RESULTS: We present fastphylo, a software package containing implementations of efficient algorithms for twocommon problems in phylogenetics: estimating DNA/protein sequence distances and reconstructing aphylogeny from a distance matrix. We compare fastphylo with other neighbor joining based methodsand report the results in terms of speed and memory efficiency.

    CONCLUSIONS: Fastphylo is a fast, memory efficient, and easy to use software suite. Due to its modular architecture,fastphylo is a flexible tool for many phylogenetic studies.

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  • 49. Khan, Mehmood Alam
    et al.
    Mahmudi, Owais
    Ullah, Ikram
    Arvestad, Lars
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Stockholm University, Science for Life Laboratory (SciLifeLab). Swedish e-Science Research Centre, Sweden.
    Lagergren, Jens
    Probabilistic inference of lateral gene transfer events2016In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 17, no Suppl 14, article id 431Article in journal (Refereed)
    Abstract [en]

    Background: Lateral gene transfer (LGT) is an evolutionary process that has an important role in biology. It challenges the traditional binary tree-like evolution of species and is attracting increasing attention of the molecular biologists due to its involvement in antibiotic resistance. A number of attempts have been made to model LGT in the presence of gene duplication and loss, but reliably placing LGT events in the species tree has remained a challenge.

    Results: In this paper, we propose probabilistic methods that samples reconciliations of the gene tree with a dated species tree and computes maximum a posteriori probabilities. The MCMC-based method uses the probabilistic model DLTRS, that integrates LGT, gene duplication, gene loss, and sequence evolution under a relaxed molecular clock for substitution rates. We can estimate posterior distributions on gene trees and, in contrast to previous work, the actual placement of potential LGT, which can be used to, e.g., identify highways of LGT.

    Conclusions: Based on a simulation study, we conclude that the method is able to infer the true LGT events on gene tree and reconcile it to the correct edges on the species tree in most cases. Applied to two biological datasets, containing gene families from Cyanobacteria and Molicutes, we find potential LGTs highways that corroborate other studies as well as previously undetected examples.

  • 50. Knight, James C.
    et al.
    Tully, Philip J.
    Kaplan, Bernhard A.
    Lansner, Anders
    Stockholm University, Faculty of Science, Numerical Analysis and Computer Science (NADA). Royal Institute of Technology, Sweden; Karolinska Institute, Sweden.
    Furber, Steve B.
    Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware2016In: Frontiers in Neuroanatomy, E-ISSN 1662-5129, Vol. 10, article id 37Article in journal (Refereed)
    Abstract [en]

    SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 2.0 x 10(4) neurons and 5.1 x 10(7) plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately 45x more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models.

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