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  • 201.
    Neveol, Aurelie
    et al.
    Univ Paris Saclay, CNRS, LIMSI, Rue John von Neumann, F-91405 Orsay, France..
    Dalianis, Hercules
    Stockholm Univ, DSV, Kista, Sweden..
    Velupillai, Sumithra
    KTH, Skolan för datavetenskap och kommunikation (CSC). Kings Coll London, Inst Psychiat Psychol & Neurosci, London, England..
    Savova, Guergana
    Childrens Hosp Boston, Boston, MA USA.;Harvard Med Sch, Boston, MA USA..
    Zweigenbaum, Pierre
    Univ Paris Saclay, CNRS, LIMSI, Rue John von Neumann, F-91405 Orsay, France..
    Clinical Natural Language Processing in languages other than English: opportunities and challenges2018Inngår i: Journal of Biomedical Semantics, ISSN 2041-1480, E-ISSN 2041-1480, Vol. 9, artikkel-id 12Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Background: Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English. Recent studies are summarized to offer insights and outline opportunities in this area. Main Body: We envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other languages, (2) NLP researchers faced with establishing clinical text processing in a language other than English, and (3) clinical informatics researchers and practitioners looking for resources in their languages in order to apply NLP techniques and tools to clinical practice and/or investigation. We review work in clinical NLP in languages other than English. We classify these studies into three groups: (i) studies describing the development of new NLP systems or components de novo, (ii) studies describing the adaptation of NLP architectures developed for English to another language, and (iii) studies focusing on a particular clinical application. Conclusion: We show the advantages and drawbacks of each method, and highlight the appropriate application context. Finally, we identify major challenges and opportunities that will affect the impact of NLP on clinical practice and public health studies in a context that encompasses English as well as other languages.

  • 202.
    Nguyen, Van Dang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Jansson, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Hoffman, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Li, Jing-Rebecca
    A partition of unity finite element method for computational diffusion MRIManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    The Bloch-Torrey equation describes the evolution of the spin (usually water proton) magnetization under the influence of applied magnetic field gradients and is commonly used in numerical simulations for diffusion MRI and NMR. Microscopic heterogeneity inside the imaging voxel is modeled by interfaces inside the simulation domain, where a discontinuity in the magnetization across the interfaces is produced via a permeability coefficient on the interfaces. To avoid having to simulate on a computational domain that is the size of an entire imaging voxel, which is often much larger than the scale of the microscopic heterogeneity as well as the mean spin diffusion displacement, smaller representative volumes of the imaging medium can be used as the simulation domain. In this case, the exterior boundaries of a representative volume either must be far away from the initial positions of the spins or suitable boundary conditions must be found to allow the movement of spins across these exterior boundaries. Many efforts have been made to solve the equation but there is still missing an efficient high performance computing framework. In this work, we present formulations of the interface as well as the exterior boundary conditions that are computationally efficient and suitable for arbitrary order finite elements and parallelization. In particular, the formulations use extended finite elements with weak enforcement of real (in the case of interior interfaces) and artificial (in the case of exterior boundaries) permeability conditions as well as operator splitting for the exterior boundary conditions. The method appears to be straightforward to implement and it is implemented in the FEniCS for moderate-scale simulations and in the FEniCS-HPC for the large-scale simulations. The accuracy of the resulting method is validated numerically and a good scalability is shown for the parallel implementation. We show that the simulated dMRI signals offer good approximations to reference signals in cases where the latter are available. Finally, we do simulations on a complex neuron to study how the signals decay under the effect of the permeable membrane and to show that the method can be used to simulate for complex geometries that we have not done before.

    Highlights:

    • The discontinuity in the magnetization across the interior interfaces of the medium is weakly imposed, allowing generalization to arbitrary order finite elements.
    • Spin exchange across the external boundaries is implemented by weakly imposing an artificial, high permeability, condition, allowing generalization to non-matching meshes.
    • Thus, optimal convergence with respect to the space discretization is achieved.
    • The second-order Crank-Nicolson method is chosen for the time discretization to reduce oscillations at high gradient strengths and allows for larger time-step sizes.
    • The method is of a high level of simplicity and suitable for parallelization.
    • An efficient open-source code is implemented in the FEniCS and FEniCS-HPC platforms.
  • 203.
    Nordling, Torbjörn E. M.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik.
    Robust inference of gene regulatory networks: System properties, variable selection, subnetworks, and design of experiments2013Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    In this thesis, inference of biological networks from in vivo data generated by perturbation experiments is considered, i.e. deduction of causal interactions that exist among the observed variables. Knowledge of such regulatory influences is essential in biology.

    A system property–interampatteness–is introduced that explains why the variation in existing gene expression data is concentrated to a few “characteristic modes” or “eigengenes”, and why previously inferred models have a large number of false positive and false negative links. An interampatte system is characterized by strong INTERactions enabling simultaneous AMPlification and ATTEnuation of different signals and we show that perturbation of individual state variables, e.g. genes, typically leads to ill-conditioned data with both characteristic and weak modes. The weak modes are typically dominated by measurement noise due to poor excitation and their existence hampers network reconstruction.

    The excitation problem is solved by iterative design of correlated multi-gene perturbation experiments that counteract the intrinsic signal attenuation of the system. The next perturbation should be designed such that the expected response practically spans an additional dimension of the state space. The proposed design is numerically demonstrated for the Snf1 signalling pathway in S. cerevisiae.

    The impact of unperturbed and unobserved latent state variables, that exist in any real biological system, on the inferred network and required set-up of the experiments for network inference is analysed. Their existence implies that a subnetwork of pseudo-direct causal regulatory influences, accounting for all environmental effects, in general is inferred. In principle, the number of latent states and different paths between the nodes of the network can be estimated, but their identity cannot be determined unless they are observed or perturbed directly.

    Network inference is recognized as a variable/model selection problem and solved by considering all possible models of a specified class that can explain the data at a desired significance level, and by classifying only the links present in all of these models as existing. As shown, these links can be determined without any parameter estimation by reformulating the variable selection problem as a robust rank problem. Solution of the rank problem enable assignment of confidence to individual interactions, without resorting to any approximation or asymptotic results. This is demonstrated by reverse engineering of the synthetic IRMA gene regulatory network from published data. A previously unknown activation of transcription of SWI5 by CBF1 in the IRMA strain of S. cerevisiae is proven to exist, which serves to illustrate that even the accumulated knowledge of well studied genes is incomplete.

  • 204.
    Nåsell, Ingemar
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.).
    The Influence of Immunity Loss on Persistence and Recurrence of Endemic Infections2013Inngår i: Bulletin of Mathematical Biology, ISSN 0092-8240, E-ISSN 1522-9602, Vol. 75, nr 11, s. 2079-2092Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Conditions for persistence of endemic infections with immunity loss are derived and shown to agree with conditions for recurrence recently established by Chaffee and Kuske (Bull. Math. Biol. 73(11):2552-2574, 2011).

  • 205.
    Oddsdottir, Hildur Aesa
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori.
    Hagrot, Erika
    KTH, Skolan för bioteknologi (BIO), Industriell bioteknologi.
    Chotteau, Veronique
    KTH, Skolan för bioteknologi (BIO), Industriell bioteknologi.
    Forsgren, Anders
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori.
    Robustness analysis of elementary flux modes generated by column generation2016Inngår i: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 273, s. 45-56Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Elementary flux modes (EFMs) are vectors defined from a metabolic reaction network, giving the connections between substrates and products. EFMs-based metabolic flux analysis (MFA) estimates the flux over each EFM from external flux measurements through least-squares data fitting. The measurements used in the data fitting are subject to errors. A robust optimization problem includes information on errors and gives a way to examine the sensitivity of the solution of the EFMs-based MFA to these errors. In general, formulating a robust optimization problem may make the problem significantly harder. We show that in the case of the EFMs-based MFA, when the errors are only in measurements and bounded by an interval, the robust problem can be stated as a convex quadratic programming (QP) problem. We have previously shown how the data fitting problem may be solved in a column-generation framework. In this paper, we show how column generation may be applied also to the robust problem, thereby avoiding explicit enumeration of EFMs. Furthermore, the option to indicate intervals on metabolites that are not measured is introduced in this column generation framework. The robustness of the data is evaluated in a case-study, which indicates that the solutions of our non-robust problems are in fact near-optimal also when robustness is considered, implying that the errors in measurement do not have a large impact on the optimal solution. Furthermore, we showed that the addition of intervals on unmeasured metabolites resulted in a change in the optimal solution.

  • 206. Omenn, Gilbert S.
    et al.
    Lane, Lydie
    Lundberg, Emma K.
    KTH, Skolan för bioteknologi (BIO). Karolinska Inst, KTH, SciLifeLab.
    Beavis, Ronald C.
    Nesvizhskii, Alexey I.
    Deutsch, Eric W.
    Metrics for the Human Proteome Project 2015: Progress on the Human Proteome and Guidelines for High-Confidence Protein Identification2015Inngår i: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 14, nr 9, s. 3452-3460Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Remarkable progress continues on the annotation of the proteins identified in the Human Proteome and on finding credible proteomic evidence for the expression of "missing proteins". Missing proteins are those with no previous protein-level evidence or insufficient evidence to make a confident identification upon reanalysis in PeptideAtlas and curation in neXtProt. Enhanced with several major new data sets published in 2014, the human proteome presented as neXtProt, version 2014-09-19, has 16 491 unique confident proteins (PE level I), up from 13 664 at 2012-12 and 15 646 at 2013-09. That leaves 2948 missing proteins from genes classified having protein existence level PE 2, 3, or 4, as well as 616 dubious proteins at PE 5. Here, we document the progress of the HPP and discuss the importance of assessing the quality of evidence, confirming automated findings and considering alternative protein matches for spectra and peptides. We provide guidelines for proteomics investigators to apply in reporting newly identified proteins.

  • 207.
    Otero, Evelyn
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Farkost och flyg, Aerodynamik. KTH Mech, Linne FLOW Ctr, SE-10044 Stockholm, Sweden.;Swedish E Sci Res Ctr SeRC, Stockholm, Sweden..
    Vinuesa, Ricardo
    KTH, Skolan för teknikvetenskap (SCI), Centra, Linné Flow Center, FLOW. KTH, Skolan för teknikvetenskap (SCI), Mekanik, Stabilitet, Transition, Kontroll. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH Mech, Linne FLOW Ctr, SE-10044 Stockholm, Sweden.;Swedish E Sci Res Ctr SeRC, Stockholm, Sweden..
    Marin, Oana
    Argonne Natl Lab, MCS, Lemont, IL 60439 USA..
    Laure, Erwin
    PDC KTH, Ctr High Performance Comp, SE-10044 Stockholm, Sweden..
    Schlatter, Philipp
    KTH, Skolan för teknikvetenskap (SCI), Centra, Linné Flow Center, FLOW. KTH, Skolan för teknikvetenskap (SCI), Mekanik, Stabilitet, Transition, Kontroll. KTH, Centra, SeRC - Swedish e-Science Research Centre. KTH, Skolan för teknikvetenskap (SCI), Mekanik, Processteknisk strömningsmekanik. KTH Mech, Linne FLOW Ctr, SE-10044 Stockholm, Sweden.;Swedish E Sci Res Ctr SeRC, Stockholm, Sweden..
    Lossy Data Compression Effects on Wall-bounded Turbulence: Bounds on Data Reduction2018Inngår i: Flow Turbulence and Combustion, ISSN 1386-6184, E-ISSN 1573-1987, Vol. 101, nr 2, s. 365-387Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Postprocessing and storage of large data sets represent one of the main computational bottlenecks in computational fluid dynamics. We assume that the accuracy necessary for computation is higher than needed for postprocessing. Therefore, in the current work we assess thresholds for data reduction as required by the most common data analysis tools used in the study of fluid flow phenomena, specifically wall-bounded turbulence. These thresholds are imposed a priori by the user in L (2)-norm, and we assess a set of parameters to identify the minimum accuracy requirements. The method considered in the present work is the discrete Legendre transform (DLT), which we evaluate in the computation of turbulence statistics, spectral analysis and resilience for cases highly-sensitive to the initial conditions. Maximum acceptable compression ratios of the original data have been found to be around 97%, depending on the application purpose. The new method outperforms downsampling, as well as the previously explored data truncation method based on discrete Chebyshev transform (DCT).

  • 208. Park, Christopher Y.
    et al.
    Klammer, Aaron A.
    Käll, Lukas
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    MacCoss, Michael J.
    Noble, William S.
    Rapid and accurate peptide identification from tandem mass spectra2008Inngår i: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 7, nr 7, s. 3022-3027Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Mass spectrometry, the core technology in the field of proteomics, promises to enable scientists to identify and quantify the entire complement of proteins in a complex biological sample. Currently, the primary bottleneck in this type of experiment is computational. Existing algorithms for interpreting mass spectra are slow and fail to identify a large proportion of the given spectra. We describe a database search program called Crux that reimplements and extends the widely used database search program Sequest. For speed, Crux uses a peptide indexing scheme to rapidly retrieve candidate peptides for a given spectrum. For each peptide in the target database, Crux generates shuffled decoy peptides on the fly, providing a good null model and, hence, accurate false discovery rate estimates. Crux also implements two recently described postprocessing methods: a p value calculation based upon fitting a Weibull distribution to the observed scores, and a semisupervised method that learns to discriminate between target and decoy matches. Both methods significantly improve the overall rate of peptide identification. Crux is implemented in C and is distributed with source code freely to noncommercial users.

  • 209.
    PAUL, DEBDAS
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Efficient Parameter Inference for Stochastic Chemical Kinetics2014Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Parameter inference for stochastic systems is considered as one of the fundamental classical problems in the domain of computational systems biology. The problem becomes challenging and often analytically intractable with the large number of uncertain parameters. In this scenario, Markov Chain Monte Carlo (MCMC) algorithms have been proved to be highly effective. For a stochastic system, the most accurate description of the kinetics is given by the Chemical Master Equation (CME). Unfortunately, analytical solution of CME is often intractable even for considerably small amount of chemically reacting species due to its super exponential state space complexity. As a solution, Stochastic Simulation Algorithm (SSA) using Monte Carlo approach was introduced to simulate the chemical process defined by the CME. SSA is an exact stochastic method to simulate CME but it also suffers from high time complexity due to simulation of every reaction. Therefore computation of likelihood function (based on exact CME) in MCMC becomes expensive which alternately makes the rejection step expensive. In this generic work, we introduce different approximations of CME as a pre-conditioning step to the full MCMC to make rejection cheaper. The goal is to avoid expensive computation of exact CME as far as possible. We show that, with effective pre-conditioning scheme, one can save a considerable amount of exact CME computations maintaining similar convergence characteristics. Additionally, we investigate three different sampling schemes (dense sampling, longer sampling and i.i.d sampling) under which convergence for MCMC using exact CME for parameter estimation can be analyzed. We find that under i.i.d sampling scheme, better convergence can be achieved than that of dense sampling of the same process or sampling the same process for longer time. We verify our theoretical findings for two different processes: linear birth-death and dimerization.Apart from providing a framework for parameter inference using CME, this work also provides us the reasons behind avoiding CME (in general) as a parameter estimation technique for so long years after its formulation

  • 210.
    Pauli, Robin
    et al.
    Julich Res Ctr, Inst Neurosci & Med INM 6, Julich, Germany.;Julich Res Ctr, Inst Adv Simulat IAS 6, Julich, Germany.;Julich Res Ctr, JARA BRAIN Inst 1, Julich, Germany..
    Weidel, Philipp
    Julich Res Ctr, Inst Neurosci & Med INM 6, Julich, Germany.;Julich Res Ctr, Inst Adv Simulat IAS 6, Julich, Germany.;Julich Res Ctr, JARA BRAIN Inst 1, Julich, Germany..
    Kunkel, Susanne
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST). Norwegian Univ Life Sci, Fac Sci & Technol, As, Norway.
    Morrison, Abigail
    Julich Res Ctr, Inst Neurosci & Med INM 6, Julich, Germany.;Julich Res Ctr, Inst Adv Simulat IAS 6, Julich, Germany.;Julich Res Ctr, JARA BRAIN Inst 1, Julich, Germany.;Ruhr Univ Bochum, Inst Cognit Neurosci, Fac Psychol, Bochum, Germany..
    Reproducing Polychronization: A Guide to Maximizing the Reproducibility of Spiking Network Models2018Inngår i: Frontiers in Neuroinformatics, ISSN 1662-5196, E-ISSN 1662-5196, Vol. 12, artikkel-id 46Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Any modeler who has attempted to reproduce a spiking neural network model from its description in a paper has discovered what a painful endeavor this is. Even when all parameters appear to have been specified, which is rare, typically the initial attempt to reproduce the network does not yield results that are recognizably akin to those in the original publication. Causes include inaccurately reported or hidden parameters (e.g., wrong unit or the existence of an initialization distribution), differences in implementation of model dynamics, and ambiguities in the text description of the network experiment. The very fact that adequate reproduction often cannot be achieved until a series of such causes have been tracked down and resolved is in itself disconcerting, as it reveals unreported model dependencies on specific implementation choices that either were not clear to the original authors, or that they chose not to disclose. In either case, such dependencies diminish the credibility of the model's claims about the behavior of the target system. To demonstrate these issues, we provide a worked example of reproducing a seminal study for which, unusually, source code was provided at time of publication. Despite this seemingly optimal starting position, reproducing the results was time consuming and frustrating. Further examination of the correctly reproduced model reveals that it is highly sensitive to implementation choices such as the realization of background noise, the integration timestep, and the thresholding parameter of the analysis algorithm. From this process, we derive a guideline of best practices that would substantially reduce the investment in reproducing neural network studies, whilst simultaneously increasing their scientific quality. We propose that this guideline can be used by authors and reviewers to assess and improve the reproducibility of future network models.

  • 211.
    Pearson, Keir
    et al.
    Univ of Alberta.
    Ekeberg, Örjan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Bueschges, Ansgar
    Univ of Köln.
    Assessing sensory function in locomotor systems using neuro-mechanical simulations2006Inngår i: TINS - Trends in Neurosciences, ISSN 0166-2236, E-ISSN 1878-108X, Vol. 29, nr 11, s. 625-631Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Computer simulations are being used increasingly to gain an understanding of the complex interactions between the neuronal, sensory, muscular and mechanical components of locomotor systems. Recent neuromechanical simulations of walking in humans, cats and insects, and of swimming in lampreys, have provided new information on the functional role of specific groups of sensory receptors in regulating locomotion. As we discuss in this review, these studies also make it clear that a full understanding of the neural and mechanical mechanisms that underlie locomotion can be achieved only by using simulations in parallel with physiological investigations. The widespread implementation of this approach would be enhanced by the development of freely available and easy-to-use software tools.

  • 212.
    Persaud, Krishna
    et al.
    The University of Manchester.
    Bernabei, Mara
    The University of Manchester.
    Benjaminsson, Simon
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Herman, Pawel
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Reverse Engineering of Nature in the field of Chemical Sensors2012Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A large scale chemical sensor array consisting of 16384 conducting polymer elements was developed emulating characteristics of the biological olfactory receptor system. A biologically realistic computational model of the olfactory cortex was developed and the data from the large array was used to test the performance of the system. Classification of odorants and segmentation of mixtures of were investigated and the results were compared to that from support vector machine algorithms.

  • 213.
    Pestana, Valeria
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Modeling drug response in cancer cell linesusing genotype and high-throughput“omics” data2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
  • 214.
    Petersson, Marcus E.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    TRPC channels activated by group 1 mG1uR in Entorhinal pyramidal neurons support integration of low frequency (<10 Hz) synaptic inputs2009Inngår i: BMC Neuroscience, ISSN 1471-2202, Vol. 10, nr Suppl 1, s. P26-Artikkel i tidsskrift (Fagfellevurdert)
  • 215.
    Petersson, Marcus E.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Stockholm, Sweden.
    Obreja, Otilia
    Lampert, Angelika
    Carr, Richard W.
    Schmelz, Martin
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Stockholm Brain Institute, Stockholm, Sweden.
    Differential Axonal Conduction Patterns of Mechano-Sensitive and Mechano-Insensitive Nociceptors - A Combined Experimental and Modelling Study2014Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, nr 8, s. e103556-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Cutaneous pain sensations are mediated largely by C-nociceptors consisting of both mechano-sensitive (CM) and mechano-insensitive (CMi) fibres that can be distinguished from one another according to their characteristic axonal properties. In healthy skin and relative to CMi fibres, CM fibres show a higher initial conduction velocity, less activity-dependent conduction velocity slowing, and less prominent post-spike supernormality. However, after sensitization with nerve growth factor, the electrical signature of CMi fibres changes towards a profile similar to that of CM fibres. Here we take a combined experimental and modelling approach to examine the molecular basis of such alterations to the excitation thresholds. Changes in electrical activation thresholds and activity-dependent slowing were examined in vivo using single-fibre recordings of CM and CMi fibres in domestic pigs following NGF application. Using computational modelling, we investigated which axonal mechanisms contribute most to the electrophysiological differences between the fibre classes. Simulations of axonal conduction suggest that the differences between CMi and CM fibres are strongly influenced by the densities of the delayed rectifier potassium channel (Kdr), the voltage-gated sodium channels Na(V)1.7 and Na(V)1.8, and the Na+/K+-ATPase. Specifically, the CM fibre profile required less K-dr and Na(V)1.8 in combination with more Na(V)1.7 and Na+/ K(+)AT-Pase. The difference between CM and CMi fibres is thus likely to reflect a relative rather than an absolute difference in protein expression. In support of this, it was possible to replicate the experimental reduction of the ADS pattern of CMi nociceptors towards a CM-like pattern following intradermal injection of nerve growth factor by decreasing the contribution of Kdr (by 50%), increasing the Na+/K+-ATPase (by 10%), and reducing the branch length from 2 cm to 1 cm. The findings highlight key molecules that potentially contribute to the NGF-induced switch in nociceptors phenotype, in particular NaV1.7 which has already been identified clinically as a principal contributor to chronic pain states such as inherited erythromelalgia.

  • 216.
    Petersson, Marcus E.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Yoshida, Motoharu
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Low-frequency summation of synaptically activated transient receptor potential channel-mediated depolarizations2011Inngår i: European Journal of Neuroscience, ISSN 0953-816X, E-ISSN 1460-9568, Vol. 34, nr 4, s. 578-593Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Neurons sum their input by spatial and temporal integration. Temporally, presynaptic firing rates are converted to dendritic membrane depolarizations by postsynaptic receptors and ion channels. In several regions of the brain, including higher association areas, the majority of firing rates are low. For rates below 20 Hz, the ionotropic receptors alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor and N-methyl-d-aspartate (NMDA) receptor will not produce effective temporal summation. We hypothesized that depolarization mediated by transient receptor potential (TRP) channels activated by metabotropic glutamate receptors would be more effective, owing to their slow kinetics. On the basis of voltage-clamp and current-clamp recordings from a rat slice preparation, we constructed a computational model of the TRP channel and its intracellular activation pathway, including the metabotropic glutamate receptor. We show that synaptic input frequencies down to 3-4 Hz and inputs consisting of as few as three to five pulses can be effectively summed. We further show that the time constant of integration increases with increasing stimulation frequency and duration. We suggest that the temporal summation characteristics of TRP channels may be important at distal dendritic arbors, where spatial summation is limited by the number of concurrently active synapses. It may be particularly important in regions characterized by low and irregular rates.

  • 217. Petrovici, Mihai A.
    et al.
    Vogginger, Bernhard
    Mueller, Paul
    Breitwieser, Oliver
    Lundqvist, Mikael
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Muller, Lyle
    Ehrlich, Matthias
    Destexhe, Alain
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Schueffny, Rene
    Schemmel, Johannes
    Meier, Karlheinz
    Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms2014Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, nr 10, s. e108590-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Advancing the size and complexity of neural network models leads to an ever increasing demand for computational resources for their simulation. Neuromorphic devices offer a number of advantages over conventional computing architectures, such as high emulation speed or low power consumption, but this usually comes at the price of reduced configurability and precision. In this article, we investigate the consequences of several such factors that are common to neuromorphic devices, more specifically limited hardware resources, limited parameter configurability and parameter variations due to fixed-pattern noise and trial-to-trial variability. Our final aim is to provide an array of methods for coping with such inevitable distortion mechanisms. As a platform for testing our proposed strategies, we use an executable system specification (ESS) of the BrainScaleS neuromorphic system, which has been designed as a universal emulation back-end for neuroscientific modeling. We address the most essential limitations of this device in detail and study their effects on three prototypical benchmark network models within a well-defined, systematic workflow. For each network model, we start by defining quantifiable functionality measures by which we then assess the effects of typical hardware-specific distortion mechanisms, both in idealized software simulations and on the ESS. For those effects that cause unacceptable deviations from the original network dynamics, we suggest generic compensation mechanisms and demonstrate their effectiveness. Both the suggested workflow and the investigated compensation mechanisms are largely back-end independent and do not require additional hardware configurability beyond the one required to emulate the benchmark networks in the first place. We hereby provide a generic methodological environment for configurable neuromorphic devices that are targeted at emulating large-scale, functional neural networks.

  • 218. Pettersen, Klas H.
    et al.
    Lindén, Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. Norwegian University of Life Sciences, Norway; University of Copenhagen, Denmark .
    Tetzlaff, Tom
    Einevoll, Gaute T.
    Power Laws from Linear Neuronal Cable Theory: Power Spectral Densities of the Soma Potential, Soma Membrane Current and Single-Neuron Contribution to the EEG2014Inngår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 10, nr 11, s. e1003928-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Power laws, that is, power spectral densities (PSDs) exhibiting 1/f(alpha) behavior for large frequencies f, have been observed both in microscopic (neural membrane potentials and currents) and macroscopic (electroencephalography; EEG) recordings. While complex network behavior has been suggested to be at the root of this phenomenon, we here demonstrate a possible origin of such power laws in the biophysical properties of single neurons described by the standard cable equation. Taking advantage of the analytical tractability of the so called ball and stick neuron model, we derive general expressions for the PSD transfer functions for a set of measures of neuronal activity: the soma membrane current, the current-dipole moment (corresponding to the single-neuron EEG contribution), and the soma membrane potential. These PSD transfer functions relate the PSDs of the respective measurements to the PSDs of the noisy input currents. With homogeneously distributed input currents across the neuronal membrane we find that all PSD transfer functions express asymptotic highfrequency 1/f(alpha) power laws with power-law exponents analytically identified as alpha(I)(infinity) =1/2 for the soma membrane current, alpha(p)(infinity) = 3/2 for the current-dipole moment, and alpha(V)(infinity) = 2 for the soma membrane potential. Comparison with available data suggests that the apparent power laws observed in the high-frequency end of the PSD spectra may stem from uncorrelated current sources which are homogeneously distributed across the neural membranes and themselves exhibit pink (1/f) noise distributions. While the PSD noise spectra at low frequencies may be dominated by synaptic noise, our findings suggest that the high-frequency power laws may originate in noise from intrinsic ion channels. The significance of this finding goes beyond neuroscience as it demonstrates how 1/f(alpha) power laws with a wide range of values for the power-law exponent a may arise from a simple, linear partial differential equation.

  • 219. Pierce, D. M.
    et al.
    Ricken, T.
    Holzapfel, Gerhard A.
    KTH, Skolan för teknikvetenskap (SCI), Hållfasthetslära (Inst.).
    Modeling sample/patient-specific structural and diffusional responses of cartilage using DT-MRI2013Inngår i: International Journal for Numerical Methods in Biomedical Engineering, ISSN 2040-7939, Vol. 29, nr 8, s. 807-821Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We propose a new 3D biphasic constitutive model designed to incorporate structural data on the sample/patient-specific collagen fiber network. The finite strain model focuses on the load-bearing morphology, that is, an incompressible, poroelastic solid matrix, reinforced by an inhomogeneous, dispersed fiber fabric, saturated with an incompressible fluid at constant electrolytic conditions residing in strain-dependent pores of the collagen-proteoglycan solid matrix. In addition, the fiber network of the solid influences the fluid permeability and an intrafibrillar portion that cannot be 'squeezed out' from the tissue. We implement the model into a finite element code. To demonstrate the utility of our proposed modeling approach, we test two hypotheses by simulating an indentation experiment for a human tissue sample. The simulations use ultra-high field diffusion tensor magnetic resonance imaging that was performed on the tissue sample. We test the following hypotheses: (i) the through-thickness structural arrangement of the collagen fiber network adjusts fluid permeation to maintain fluid pressure (Biomech. Model. Mechanobiol. 7: 367-378, 2008); and (ii) the inhomogeneity of mechanical properties through the cartilage thickness acts to maintain fluid pressure at the articular surface (J. Biomech. Eng. 125: 569-577, 2003). For the tissue sample investigated, both through-thickness inhomogeneities of the collagen fiber distribution and of the material properties serve to influence the interstitial fluid pressure distribution and maintain fluid pressure underneath the indenter at the cartilage surface. Tissue inhomogeneity appears to have a larger effect on fluid pressure retention in this tissue sample and on the advantageous pressure distribution.

  • 220. Pierce, David M.
    et al.
    Ricken, Tim
    Holzapfel, Gerhard A.
    KTH, Skolan för teknikvetenskap (SCI), Hållfasthetslära (Inst.). Institute of Biomechanics, Center of Biomedical Engineering, Graz University of Technology.
    A hyperelastic biphasic fibre-reinforced model of articular cartilage considering distributed collagen fibre orientations: continuum basis, computational aspects and applications2013Inngår i: Computer Methods in Biomechanics and Biomedical Engineering, ISSN 1025-5842, E-ISSN 1476-8259, Vol. 16, nr 12, s. 1344-1361Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Cartilage is a multi-phase material composed of fluid and electrolytes (68-85% by wet weight), proteoglycans (5-10% by wet weight), chondrocytes, collagen fibres and other glycoproteins. The solid phase constitutes an isotropic proteoglycan gel and a fibre network of predominantly type II collagen, which provides tensile strength and mechanical stiffness. The same two components control diffusion of the fluid phase, e.g. as visualised by diffusion tensor MRI: (i) the proteoglycan gel (giving a baseline isotropic diffusivity) and (ii) the highly anisotropic collagenous fibre network. We propose a new constitutive model and finite element implementation that focus on the essential load-bearing morphology: an incompressible, poroelastic solid matrix reinforced by an inhomogeneous, dispersed fibre fabric, which is saturated with an incompressible fluid residing in strain-dependent pores of the collagen-proteoglycan solid matrix. The inhomogeneous, dispersed fibre fabric of the solid further influences the fluid permeability, as well as an intrafibrillar portion that cannot be squeezed out' from the tissue. Using representative numerical examples on the mechanical response of cartilage, we reproduce several features that have been demonstrated experimentally in the cartilage mechanics literature.

  • 221. Pons, Carles
    et al.
    Jimenez-Gonzalez, Daniel
    Gonzalez-Alvarez, Cecilia
    Servat, Harald
    Cabrera-Benitez, Daniel
    Aguilar, Xavier
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC.
    Fernandez-Recio, Juan
    Cell-Dock: high-performance protein-protein docking2012Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 28, nr 18, s. 2394-2396Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The application of docking to large-scale experiments or the explicit treatment of protein flexibility are part of the new challenges in structural bioinformatics that will require large computer resources and more efficient algorithms. Highly optimized fast Fourier transform (FFT) approaches are broadly used in docking programs but their optimal code implementation leaves hardware acceleration as the only option to significantly reduce the computational cost of these tools. In this work we present Cell-Dock, an FFT-based docking algorithm adapted to the Cell BE processor. We show that Cell-Dock runs faster than FTDock with maximum speedups of above 200x, while achieving results of similar quality.

  • 222. Prezza, N.
    et al.
    Del Fabbro, C.
    Vezzi, Francesco
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    De Paoli, E.
    Policriti, A.
    ERNE-BS5: Aligning BS-treated sequences by multiple hits on a 5-letters alphabet2012Inngår i: BCB '12 Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM , 2012, s. 12-19Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Cytosine methylation is a DNA modification that has great impact on the regulation of gene expression and important implications for the biology and health of several living beings, including humans. Bisulfite conversion followed by next generation sequencing (BS-seq) of DNA is the gold standard technique used to detect DNA methylation at single-base resolution on a genome scale through the identification of 5-methylcytosine (5-mC). However, by converting unmethylated cytosines into thymines, BS-seq poses computational challenges to read alignment and aggravates the issue of multiple hits due to the ambiguity raised by the reduced sequence complexity. Here we present ERNE-BS5 (Extended Randomized Numerical alignEr - BiSulfite 5 ), an aligning program developed to efficiently map BS-treated reads against large genomes (e.g., human). To achieve this goal we have implemented three different ideas: (i) we use a 5-letters alphabet for storing methylation information, (ii) we use a weighted context-aware Hamming distance to identify a T coming from an unmethylated C context, and (iii) we use an iterative process to position multiple-hit reads starting from a preliminary map built using single-hit alignments. The map is corrected and extended at each cycle using the alignments added in the previous iteration. ERNE-BS5 is based on a new improved version of the rNA [20] aligning software with a more efficient core. ERNE (Extended Randomized Numerical alignEr) is a short string alignment package whose goal is to provide an all-inclusive set of tools to handle short reads. ERNE comprises: ERNE-MAP, ERNE-DMAP, ERNEFILTER, ERNE-VISUAL, and, from now on, ERNE-BS5. ERNE is free software and distributed with an Open Source License (GPL V3) and can be downloaded at: http://erne.sourceforge.net.

  • 223. Qu, Hong
    et al.
    Xing, Ke
    Takacs, Alexander
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots2013Inngår i: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 120, s. 509-517Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper presents a Co-evolutionary Improved Genetic Algorithm (CIGA) for global path planning of multiple mobile robots, which employs a co-evolution mechanism together with an improved genetic algorithm (GA). This improved GA presents an effective and accurate fitness function, improves genetic operators of conventional genetic algorithms and proposes a new genetic modification operator. Moreover, the improved GA, compared with conventional GAs, is better at avoiding the problem of local optimum and has an accelerated convergence rate. The use of a co-evolution mechanism takes into full account the cooperation between populations, which avoids collision between mobile robots and is conductive for each mobile robot to obtain an optimal or near-optimal collision-free path. Simulations are carried out to demonstrate the efficiency of the improved GA and the effectiveness of CIGA.

  • 224.
    Rajarathinam, Kayathri
    KTH, Skolan för bioteknologi (BIO), Teoretisk kemi och biologi.
    Nutraceuticals based computational medicinal chemistry2013Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    In recent years, the edible biomedicinal products called nutraceuticals have been becoming more popular among the pharmaceutical industries and the consumers. In the process of developing nutraceuticals, in silico approaches play an important role in structural elucidation, receptor-ligand interactions, drug designing etc., that critically help the laboratory experiments to avoid biological and financial risk. In this thesis, three nutraceuticals possessing antimicrobial and anticancer activities have been studied. Firstly, a tertiary structure was elucidated for a coagulant protein (MO2.1) of Moringa oleifera based on homology modeling and also studied its oligomerization that is believed to interfere with its medicinal properties. Secondly, the antimicrobial efficiency of a limonoid from neem tree called ‘azadirachtin’ was studied with a bacterial (Proteus mirabilis) detoxification agent, glutathione S-transferase, to propose it as a potent drug candidate for urinary tract infections. Thirdly, sequence specific binding activity was analyzed for a plant alkaloid called ‘palmatine’ for the purpose of developing intercalators in cancer therapy. Cumulatively, we have used in silico methods to propose the structure of an antimicrobial peptide and also to understand the interactions between protein and nucleic acids with these nutraceuticals.

  • 225.
    Ray, Arjun
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Teoretisk fysik. KTH, Centra, SeRC - Swedish e-Science Research Centre.
    Lindahl, Erik
    KTH, Skolan för teknikvetenskap (SCI), Teoretisk fysik, Beräkningsbiofysik. KTH, Centra, SeRC - Swedish e-Science Research Centre.
    Wallner, B.
    Improved model quality assessment using ProQ22012Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 13, nr 1, s. 224-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Employing methods to assess the quality of modeled protein structures is now standard practice in bioinformatics. In a broad sense, the techniques can be divided into methods relying on consensus prediction on the one hand, and single-model methods on the other. Consensus methods frequently perform very well when there is a clear consensus, but this is not always the case. In particular, they frequently fail in selecting the best possible model in the hard cases (lacking consensus) or in the easy cases where models are very similar. In contrast, single-model methods do not suffer from these drawbacks and could potentially be applied on any protein of interest to assess quality or as a scoring function for sampling-based refinement.Results: Here, we present a new single-model method, ProQ2, based on ideas from its predecessor, ProQ. ProQ2 is a model quality assessment algorithm that uses support vector machines to predict local as well as global quality of protein models. Improved performance is obtained by combining previously used features with updated structural and predicted features. The most important contribution can be attributed to the use of profile weighting of the residue specific features and the use features averaged over the whole model even though the prediction is still local.Conclusions: ProQ2 is significantly better than its predecessors at detecting high quality models, improving the sum of Z-scores for the selected first-ranked models by 20% and 32% compared to the second-best single-model method in CASP8 and CASP9, respectively. The absolute quality assessment of the models at both local and global level is also improved. The Pearson's correlation between the correct and local predicted score is improved from 0.59 to 0.70 on CASP8 and from 0.62 to 0.68 on CASP9; for global score to the correct GDT_TS from 0.75 to 0.80 and from 0.77 to 0.80 again compared to the second-best single methods in CASP8 and CASP9, respectively. ProQ2 is available at http://proq2.wallnerlab.org.

  • 226.
    Rehn, Erik M
    et al.
    Bernstein Center for Computational Neuroscience.
    Benjaminsson, Simon
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Event-based Sensor Interface for Supercomputer scale Neural Networks2012Rapport (Annet vitenskapelig)
  • 227.
    Reimegård, Johan
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Kundu, Snehangshu
    Pendle, Ali
    Irish, Vivian F
    Shaw, Peter
    Nakayama, Naomi
    Sundström, Jens F
    Emanuelsson, Olof
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Genome-wide identification of physically clustered genes suggests chromatin-level co-regulation in male reproductive development in Arabidopsis thaliana2017Inngår i: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Co-expression of physically linked genes occurs surprisingly frequently in eukaryotes. Such chromosomal clustering may confer a selective advantage as it enables coordinated gene regulation at the chromatin level. We studied the chromosomal organization of genes involved in male reproductive development in Arabidopsis thaliana. We developed an in-silico tool to identify physical clusters of co-regulated genes from gene expression data. We identified 17 clusters (96 genes) involved in stamen development and acting downstream of the transcriptional activator MS1 (MALE STERILITY 1), which contains a PHD domain associated with chromatin re-organization. The clusters exhibited little gene homology or promoter element similarity, and largely overlapped with reported repressive histone marks. Experiments on a subset of the clusters suggested a link between expression activation and chromatin conformation: qRT-PCR and mRNA in situ hybridization showed that the clustered genes were up-regulated within 48 h after MS1 induction; out of 14 chromatin-remodeling mutants studied, expression of clustered genes was consistently down-regulated only in hta9/hta11, previously associated with metabolic cluster activation; DNA fluorescence in situ hybridization confirmed that transcriptional activation of the clustered genes was correlated with open chromatin conformation. Stamen development thus appears to involve transcriptional activation of physically clustered genes through chromatin de-condensation.

  • 228. Reynolds, Sheila M.
    et al.
    Käll, Lukas
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Riffle, Michael E.
    Bilmes, Jeff A.
    Noble, William Stafford
    Transmembrane topology and signal peptide prediction using dynamic bayesian networks2008Inngår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 4, nr 11, s. e1000213-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by a previously published HMM, Phobius, and combines a signal peptide submodel with a transmembrane submodel. We introduce a two-stage DBN decoder that combines the power of posterior decoding with the grammar constraints of Viterbi-style decoding. Philius also provides protein type, segment, and topology confidence metrics to aid in the interpretation of the predictions. We report a relative improvement of 13% over Phobius in full-topology prediction accuracy on transmembrane proteins, and a sensitivity and specificity of 0.96 in detecting signal peptides. We also show that our confidence metrics correlate well with the observed precision. In addition, we have made predictions on all 6.3 million proteins in the Yeast Resource Center (YRC) database. This large-scale study provides an overall picture of the relative numbers of proteins that include a signal-peptide and/or one or more transmembrane segments as well as a valuable resource for the scientific community. All DBNs are implemented using the Graphical Models Toolkit. Source code for the models described here is available at http://noble.gs.washington.edu/proj/philius. A Philius Web server is available at http://www.yeastrc.org/philius, and the predictions on the YRC database are available at http://www.yeastrc.org/pdr.

  • 229. Roland, P
    et al.
    Svensson, Gert
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Risch, T
    Baumann, P
    Dehmel, A
    Fredriksson, Jesper
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Halldorson, Hjörleifur
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Forsberg, Lars
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Young, J
    Zilles, Karl
    A database generator for human brain imaging2001Inngår i: TINS - Trends in Neurosciences, ISSN 0166-2236, E-ISSN 1878-108X, Vol. 24, nr 10, s. 562-564Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Sharing scientific data containing complex information requires new concepts and new technology. NEUROGENERATOR is a database generator for the neuroimaging community. A database generator is a database that generates new databases. The scientists submit raw PET and fMRI data to NEUROGENERATOR, which then processes the data in a uniform way to create databases of homogenous data suitable for data sharing, met-analysis and modelling the human brain at the systems level. These databases are then distributed to the scientists.

  • 230. Rosbacke, M.
    et al.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Björkman, E.
    Roland, P. E.
    Evaluation of using absolute versus relative base level when analyzing brain activation images using the scale-space primal sketch2001Inngår i: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 5, nr 2, s. 89-110Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A dominant approach to brain mapping is to define functional regions in the brain by analyzing images of brain activation obtained from positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). This paper presents an evaluation of using one such tool, called the scale-space primal sketch, for brain activation analysis. A comparison is made concerning two possible definitions of a significance measure of blob structures in scale-space, where local contrast is measured either relative to a local or global reference level. Experiments on real brain data show that (i) the global approach with absolute base level has a higher degree of correspondence to a traditional statistical method than a local approach with relative base level, and that (ii) the global approach with absolute base level gives a higher significance to small blobs that are superimposed on larger scale structures, whereas the significance of isolated blobs largely remains unaffected. Relative to previously reported works, the following two technical improvements are also presented. (i) A post-processing tool is introduced for merging blobs that are multiple responses to image structures. This simplifies automated analysis from the scale-space primal sketch. (ii) A new approach is introduced for scale-space normalization of the significance measure, by collecting reference statistics of residual noise images obtained from the general Linear model.

  • 231.
    Sahlin, Kristoffer
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Algorithms and statistical models for scaffolding contig assemblies and detecting structural variants using read pair data2015Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Advances in throughput from Next Generation Sequencing (NGS) methods has provided new ways to study molecular biology. The increased amount of data enables genome wide scale studies of structural variation, transcription, translation and genome composition. Not only is the scale of each experiment large; lowered cost and faster turn-around has also increased the frequency with which new experiments are conducted. With the data growth comes an increase in demand for efficient and robust algorithms — this is a great computational challenge. The design of computationally efficient algorithms are crucial to cope with the amount of data and it is relatively easy to verify an efficient algorithm by runtime and memory consumption. However, as NGS data comes with several artifacts together with the size the difficulty lies in verifying that the algorithm gives accurate results and are robust to different data sets.

    This thesis focuses on modeling assumptions of mate-pair and paired-end reads when scaffolding contig assemblies or detecting variants. Both genome assembly and structural variation are difficult problems, partly because of a computationally complex nature of the problems, but also due to various noise and artifacts in input data. Constructing methods that addresses all artifacts and parameters in data is difficult, if not impossible, and end-to-end pipelines often come with several simplifications. Instead of tackling these difficult problems all at once, a large part of this thesis concentrates on smaller problems around scaffolding and structural variation detection. By identifying and modeling parts of the problem where simplifications has been made in other algorithms, we obtain an improved solution to the corresponding full problem.

    The first paper shows an improved model to estimate gap sizes, hence contig placement, in the scaffolding problem. The second paper introduces a new scaffolder to scaffold large complex genomes and the third paper extends the scaffolding method to account for paired-end-contamination in mate-pair libraries. The fourth paper investigates detection of structural variants using fragment length information and corrects a commonly assumed null-hypothesis distribution used to detect structural variants.

  • 232.
    Sahlin, Kristoffer
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Chikhi, Rayan
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Genome scaffolding with PE-contaminated mate-pair libraries2015Manuskript (preprint) (Annet vitenskapelig)
  • 233.
    Sahlin, Kristoffer
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Frånberg, M.
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). KTH, Centra, SeRC - Swedish e-Science Research Centre. Stockholm University, Sweden.
    Structural Variation Detection with Read Pair Information: An Improved Null Hypothesis Reduces Bias2017Inngår i: Journal of Computational Biology, ISSN 1066-5277, E-ISSN 1557-8666, Vol. 24, nr 6, s. 581-589Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Reads from paired-end and mate-pair libraries are often utilized to find structural variation in genomes, and one common approach is to use their fragment length for detection. After aligning read pairs to the reference, read pair distances are analyzed for statistically significant deviations. However, previously proposed methods are based on a simplified model of observed fragment lengths that does not agree with data. We show how this model limits statistical analysis of identifying variants and propose a new model by adapting a model we have previously introduced for contig scaffolding, which agrees with data. From this model, we derive an improved null hypothesis that when applied in the variant caller CLEVER, reduces the number of false positives and corrects a bias that contributes to more deletion calls than insertion calls. We advise developers of variant callers with statistical fragment length-based methods to adapt the concepts in our proposed model and null hypothesis.

  • 234.
    Sahlin, Kristoffer
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Frånberg, Mattias
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Correcting bias from stochastic insert size in read pair data—applications to structural variation detection and genome assembly2015Manuskript (preprint) (Annet vitenskapelig)
  • 235. Salmela, L.
    et al.
    Sahlin, Kristoffer
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Mäkinen, V.
    Tomescu, A. I.
    Gap filling as exact path length problem2015Inngår i: Research in Computational Molecular Biology. 19th Annual International Conference, RECOMB 2015. Proceedings, 2015, s. 281-292Konferansepaper (Fagfellevurdert)
    Abstract [en]

    One of the last steps in a genome assembly project is filling the gaps between consecutive contigs in the scaffolds. This problem can be naturally stated as finding an s-t path in a directed graph whose sum of arc costs belongs to a given range (the estimate on the gap length). Here s and t are any two contigs flanking a gap. This problem is known to be NP-hard in general. Here we derive a simpler dynamic programming solution than already known, pseudo-polynomial in the maximum value of the input range. We implemented various practical optimizations to it, and compared our exact gap filling solution experimentally to popular gap filling tools. Summing over all the bacterial assemblies considered in our experiments, we can in total fill 28% more gaps than the best previous tool and the gaps filled by our method span 80% more sequence. Furthermore, the error level of the newly introduced sequence is comparable to that of the previous tools.

  • 236. Salmela, Leena
    et al.
    Sahlin, Kristoffer
    Makinen, Veli
    Tomescu, Alexandru I.
    Gap Filling as Exact Path Length Problem2016Inngår i: Journal of Computational Biology, ISSN 1066-5277, E-ISSN 1557-8666, Vol. 23, nr 5, s. 347-361Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    One of the last steps in a genome assembly project is filling the gaps between consecutive contigs in the scaffolds. This problem can be naturally stated as finding an s-t path in a directed graph whose sum of arc costs belongs to a given range (the estimate on the gap length). Here s and t are any two contigs flanking a gap. This problem is known to be NP-hard in general. Here we derive a simpler dynamic programming solution than already known, pseudo-polynomial in the maximum value of the input range. We implemented various practical optimizations to it, and compared our exact gap-filling solution experimentally to popular gap-filling tools. Summing over all the bacterial assemblies considered in our experiments, we can in total fill 76% more gaps than the best previous tool, and the gaps filled by our method span 136% more sequence. Furthermore, the error level of the newly introduced sequence is comparable to that of the previous tools. The experiments also show that our exact approach does not easily scale to larger genomes, where the problem is in general difficult for all tools.

  • 237.
    Sandberg, Anders
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    An autocatalytic model of STDP timing from slow calcium-dependent signals2005Inngår i: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 65-66, s. 603-608Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Data of spike timing-dependent plasticity (STDP) show a sharp temporal transition between potentiation and depression despite a relatively slow time course of calcium concentration. We show how autocatalytic amplification of initial concentration differences can enable a high degree of temporal selectivity and produce the sharp STDP weight change curve despite having a relatively slow time constant. This simple model is robust to parameter changes, noise and details of the model. The model correctly predicts the location of the maximum and minimum for STDP at +/- 10ms from coincidence.

  • 238.
    Sandberg, Anders
    et al.
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Lansner, Anders
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Petersson, K. M.
    Ekeberg, Örjan
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    A Bayesian attractor network with incremental learning2002Inngår i: Network, ISSN 0954-898X, E-ISSN 1361-6536, Vol. 13, nr 2, s. 179-194Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A realtime online learning system with capacity limits needs to gradually forget old information in order to avoid catastrophic forgetting. This can be achieved by allowing new information to overwrite old, as in a so-called palimpsest memory. This paper describes an incremental learning rule based on the Bayesian confidence propagation neural network that has palimpsest properties when employed in an attractor neural network. The network does not suffer from catastrophic forgetting, has a capacity dependent on the learning time constant and exhibits faster convergence for newer patterns.

  • 239.
    Sandberg, Anders
    et al.
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Lansner, Anders
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Petersson, K. M.
    Ekeberg, Örjan
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    A palimpsest memory based on an incremental Bayesian learning rule2000Inngår i: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 32, s. 987-994Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Capacity limited memory systems need to gradually forget old information in order to avoid catastrophic forgetting where all stored information is lost. This can be achieved by allowing new information to overwrite old, as in the so-called palimpsest memory. This paper describes a new such learning rule employed in an attractor neural network. The network does not exhibit catastrophic forgetting, has a capacity dependent on the learning time constant and exhibits recency effects in retrieval.

  • 240. Sastry, Anand
    et al.
    Monk, Jonathan
    Tegel, Hanna
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. Technical University of Denmark - DTU.
    Pålsson, Bernhard O.
    Rockberg, Johan
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Brunk, Elizabeth
    Machine learning in computational biology to accelerate high-throughput protein expression2017Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 33, nr 16, s. 2487-2495Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Motivation: The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Results: Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation.

  • 241. Schain, Martin
    et al.
    Benjaminsson, Simon
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Varnas, Katarina
    Forsberg, Anton
    Halldin, Christer
    Lansner, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Farde, Lars
    Varrone, Andrea
    Image derived input function using a multivariate analysis method based on pair-wise correlation between PET-image voxels2012Inngår i: Journal of Cerebral Blood Flow and Metabolism, ISSN 0271-678X, E-ISSN 1559-7016, Vol. 32, s. S149-S151Artikkel i tidsskrift (Annet vitenskapelig)
  • 242. Shakya, S.
    et al.
    Batool, Nazre
    KTH, Skolan för teknik och hälsa (STH).
    Özarslan, E.
    Knutsson, H.
    Multi-fiber reconstruction using probabilistic mixture models for diffusion MRI examinations of the brain2017Inngår i: Modeling, Analysis, and Visualization of Anisotropy, Springer Berlin/Heidelberg, 2017, nr 9783319613574, s. 283-308Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    In the field of MRI brain image analysis, Diffusion tensor imaging (DTI) provides a description of the diffusion of water through tissue and makes it possible to trace fiber connectivity in the brain, yielding a map of how the brain is wired. DTI employs a second order diffusion tensor model based on the assumption of Gaussian diffusion. The Gaussian assumption, however, limits the use of DTI in solving intra-voxel fiber heterogeneity as the diffusion can be non-Gaussian in several biological tissues including human brain. Several approaches to modeling the non-Gaussian diffusion and intra-voxel fiber heterogeneity reconstruction have been proposed in the last decades. Among such approaches are the multi-compartmental probabilistic mixture models. These models include the discrete or continuous mixtures of probability distributions such as Gaussian, Wishart or von Mises-Fisher distributions. Given the diffusion weighted MRI data, the problem of resolving multiple fibers within a single voxel boils down to estimating the parameters of such models. In this chapter, we focus on such multi-compartmental probabilistic mixture models. First we present a review including mathematical formulations of the most commonly applied mixture models. Then, we present a novel method based on the mixture of non-central Wishart distributions. A mixture model of central Wishart distributions has already been proposed earlier to resolve intra-voxel heterogeneity. However, we show with detailed experiments that our proposed model outperforms the previously proposed probabilistic models specifically for the challenging scenario when the separation angles between crossing fibers (two or three) are small. We compare our results with the recently proposed probabilistic models of mixture of central Wishart distributions and mixture of hyper-spherical von Mises-Fisher distributions. We validate our approach with several simulations including fiber orientations in two and three directions and with real data. Resistivity to noise is also demonstrated by increasing levels of Rician noise in simulated data. The experiments demonstrate the superior performance of our proposed model over the prior probabilistic mixture models.

  • 243.
    Sjöstrand, Joel
    et al.
    Dept. of Numerical Analysis and Computer Science, Stockholm University.
    Sennblad, Bengt
    Karolinska Institutet.
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    DLRS: gene tree evolution in light of a species tree2012Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 28, nr 22, s. 2994-2995Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    PrIME-DLRS (or colloquially: 'Delirious') is a phylogenetic software tool to simultaneously infer and reconcile a gene tree given a species tree. It accounts for duplication and loss events, a relaxed molecular clock and is intended for the study of homologous gene families, for example in a comparative genomics setting involving multiple species. PrIME-DLRS uses a Bayesian MCMC framework, where the input is a known species tree with divergence times and a multiple sequence alignment, and the output is a posterior distribution over gene trees and model parameters.

  • 244. Spivak, Marina
    et al.
    Weston, Jason
    Bottou, Léon
    Käll, Lukas
    Noble, William Stafford
    Improvements to the percolator algorithm for Peptide identification from shotgun proteomics data sets2009Inngår i: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 8, nr 7, s. 3737-3745Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Shotgun proteomics coupled with database search software allows the identification of a large number of peptides in a single experiment. However, some existing search algorithms, such as SEQUEST, use score functions that are designed primarily to identify the best peptide for a given spectrum. Consequently, when comparing identifications across spectra, the SEQUEST score function Xcorr fails to discriminate accurately between correct and incorrect peptide identifications. Several machine learning methods have been proposed to address the resulting classification task of distinguishing between correct and incorrect peptide-spectrum matches (PSMs). A recent example is Percolator, which uses semisupervised learning and a decoy database search strategy to learn to distinguish between correct and incorrect PSMs identified by a database search algorithm. The current work describes three improvements to Percolator. (1) Percolator's heuristic optimization is replaced with a clear objective function, with intuitive reasons behind its choice. (2) Tractable nonlinear models are used instead of linear models, leading to improved accuracy over the original Percolator. (3) A method, Q-ranker, for directly optimizing the number of identified spectra at a specified q value is proposed, which achieves further gains.

  • 245.
    Sullivan, Devin
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Carnegie Mellon University, Pittsburgh, PA, United States.
    Murphy, R. F.
    Tapia, J. -J
    Dittrich, M.
    Arepally, R.
    Faeder, J. R.
    Design automation for biological models: A pipeline that incorporates spatial and molecular complexity2015Inngår i: Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI, ACM Press, 2015, Vol. 20-22-May-2015, s. 321-323Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Understanding the dynamics of biochemical networks is a major goal of systems biology. Due to the heterogeneity of cells and the low copy numbers of key molecules, spatially resolved approaches are required to fully understand and model these systems. Until recently, most spatial modeling was performed using geometries obtained either through manual segmentation or manual fabrication both of which are time-consuming and tedious. Similarly, the system of reactions associated with the model had to be manually defined, a process that is both tedious and error-prone for large networks. As a result, spatially resolved simulations have typically only been performed in a limited number of geometries, which are often highly simplified, and with small reaction networks.

  • 246.
    Sweeney, Yann
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). School of Informatics, University of Edinburgh, UK.
    Functional Relevance of Homeostatic Intrinsic Plasticity in Neurons and Networks2016Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Maintaining the intrinsic excitability of neurons is crucial for stable brain activity. This can be achieved by the homeostatic regulation of membrane ion channel conductances, although it is not well understood how these processes influence broader aspects of neuron and network function. One of the many mechanisms which contribute towards this task is the modulation of potassium channel conductances by activity-dependent nitric oxide signalling. Here, we first investigate this mechanism in a conductance-based neuron model. By fitting the model to experimental data we find that nitric oxide signalling improves synaptic transmission fidelity at high firing rates, but that there is an increase in the metabolic cost of action potentials associated with this improvement. Although the improvement in function had been observed previously in experiment, the metabolic constraint was unknown. This additional constraint provides a plausible explanation for the selective activation of nitric oxide signalling only at high firing rates. In addition to mediating homeostatic control of intrinsic excitability, nitric oxide can diffuse freely across cell membranes, providing a unique mechanism for neurons to communicate within a network, independent of synaptic connectivity. We next conduct a theoretical investigation of the distinguishing roles of diffusive homeostasis mediated by nitric oxide in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis robustly maintain stable activity. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that diffusive homeostasis interferes less than non-diffusive homeostasis in the synaptic weight dynamics of networks undergoing Hebbian plasticity. Overall, these results suggest a novel homeostatic mechanism for maintaining stable network activity while simultaneously minimising metabolic cost and conserving network functionality.

  • 247. Szalisznyo, Krisztina
    et al.
    Silverstein, David N.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC.
    Duffau, Hugues
    Smits, Anja
    Pathological Neural Attractor Dynamics in Slowly Growing Gliomas Supports an Optimal Time Frame for White Matter Plasticity2013Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, nr 7, s. e69798-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Neurological function in patients with slowly growing brain tumors can be preserved even after extensive tumor resection. However, the global process of cortical reshaping and cerebral redistribution cannot be understood without taking into account the white matter tracts. The aim of this study was to predict the functional consequences of tumor-induced white matter damage by computer simulation. A computational model was proposed, incorporating two cortical patches and the white matter connections of the uncinate fasciculus. Tumor-induced structural changes were modeled such that different aspects of the connectivity were altered, mimicking the biological heterogeneity of gliomas. The network performance was quantified by comparing memory pattern recall and the plastic compensatory capacity of the network was analyzed. The model predicts an optimal level of synaptic conductance boost that compensates for tumor-induced connectivity loss. Tumor density appears to change the optimal plasticity regime, but tumor size does not. Compensatory conductance values that are too high lead to performance loss in the network and eventually to epileptic activity. Tumors of different configurations show differences in memory recall performance with slightly lower plasticity values for dense tumors compared to more diffuse tumors. Simulation results also suggest an optimal noise level that is capable of increasing the recall performance in tumor-induced white matter damage. In conclusion, the model presented here is able to capture the influence of different tumor-related parameters on memory pattern recall decline and provides a new way to study the functional consequences of white matter invasion by slowly growing brain tumors.

  • 248. Szalisznyó, K.
    et al.
    Silverstein, David N.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST).
    Tóth, J.
    Neural dynamics in co-morbid schizophrenia and OCD: A computational approach2019Inngår i: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 473, s. 80-94Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The co-morbidity of obsessive-compulsive disorder (OCD) and schizophrenia is higher than what would be expected by chance and the common underlying neuropathophysiology is not well understood. Repetitive stereotypes and routines can be caused by perseverative thoughts and motor sequences in both of these disorders. We extended a previously published computational model to investigate cortico-striatal network dynamics. Given the considerable overlap in symptom phenomenology and the high degree of co-morbidity between OCD and schizophrenia, we examined the dynamical consequences of functional connectivity variations in the overlapping network. This was achieved by focusing on the emergence of network oscillatory activity and examining parameter sensitivity. Opposing activity levels are present in orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC) in schizophrenia and OCD. We found that with over-compensation of the primary pathology, emergence of the other disorder can occur. The oscillatory behavior is delicately modulated by connections between the OFC/ACC to the ventral and dorsal striatum and by the coupling between the ACC and dorsolateral prefrontal cortex (DLPFC). Modulation on cortical self-inhibition (e.g. serotonin reuptake inhibitor treatment) together with dopaminergic input to the striatum (e.g. anti-dopaminergic medication) has non-trivial complex effects on the network oscillatory behavior, with an optimal modulatory window. Additionally, there are several disruption mechanisms and compensatory processes in the cortico-striato-thalamic network which may contribute to the underlying neuropathophysiology and clinical heterogeneity in schizo-obsessive spectrum disorders. Our mechanistic model predicts that dynamic over-compensation of the primarily occuring neuropathophysiology can lead to the secondary co-morbid disease.

  • 249. Tahvildari, Babak
    et al.
    Fransén, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Alonso, Angel A.
    Hasselmo, Michael E.
    Switching between on and off states of persistent activity in lateral entorhinal layer III neurons2007Inngår i: Hippocampus, ISSN 1050-9631, E-ISSN 1098-1063, Vol. 17, nr 4, s. 257-263Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Persistent neural spiking maintains information during a, working memory task when a stimulus is no longer present. During I retention, this activity needs to be stable to distractors. More importantly, when retention is no longer relevant, cessation of the activity is necessary to enable processing and retention of subsequent information. Here, by means of intracellular recording with sharp microelectrode in in vitro rat brain slices, we demonstrate that single principal layer III neurons of the lateral entorhinal cortex (EC) generate persistent spiking activity with a novel ability to reliably toggle between spiking activity and a silent state. Our data indicates that in the presence of muscarmic receptor activation, persistent activity following an excitatory input may be induced and that a subsequent excitatory input can terminate this activity and cause the neuron to return to a silent state. Moreover, application of inhibitory hyperpolarizing stimuli is neither able to decrease the frequency of the persistent activity nor terminate it. The persistent activity can also be initiated and terminated by synchronized synaptic stimuli of layer II/III of the perirhinal cortex. The neuronal ability to switch On and Off persistent activity may facilitate the concurrent representation of temporally segregated information arriving in the EC and being directed toward the hippocampus.

  • 250. Tarjuelo-Gutierrez, J.
    et al.
    Rodriguez-Vila, B.
    Pierce, D. M.
    Fastl, T. E.
    Verbrugghe, P.
    Fourneau, I.
    Maleux, G.
    Herijgers, P.
    Holzapfel, Gerhard A.
    KTH, Skolan för teknikvetenskap (SCI), Hållfasthetslära (Inst.).
    Gomez, E. J.
    High-quality conforming hexahedral meshes of patient-specific abdominal aortic aneurysms including their intraluminal thrombi2014Inngår i: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 52, nr 2, s. 159-168Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In order to perform finite element (FE) analyses of patient-specific abdominal aortic aneurysms, geometries derived from medical images must be meshed with suitable elements. We propose a semi-automatic method for generating conforming hexahedral meshes directly from contours segmented from medical images. Magnetic resonance images are generated using a protocol developed to give the abdominal aorta high contrast against the surrounding soft tissue. These data allow us to distinguish between the different structures of interest. We build novel quadrilateral meshes for each surface of the sectioned geometry and generate conforming hexahedral meshes by combining the quadrilateral meshes. The three-layered morphology of both the arterial wall and thrombus is incorporated using parameters determined from experiments. We demonstrate the quality of our patient-specific meshes using the element Scaled Jacobian. The method efficiently generates high-quality elements suitable for FE analysis, even in the bifurcation region of the aorta into the iliac arteries. For example, hexahedral meshes of up to 125,000 elements are generated in less than 130 s, with 94.8 % of elements well suited for FE analysis. We provide novel input for simulations by independently meshing both the arterial wall and intraluminal thrombus of the aneurysm, and their respective layered morphologies.

23456 201 - 250 of 288
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