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26th Annual computational Neuroscience Meeting (CNS*2017) of the Organization for computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Optimal control for a discrete time influenza model

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2nd Colombian Congress on computational Biology and Bioinformatics, CCBCOL 2013

作者： Parra, Paula Andrea Gonzalez Ceberio, Martine Lee, Sunmi Castillo-Chavez, Carlos Universidad Autónoma de Occidente Departamento de Matematicas Cali Colombia The University of Texas at El Paso Computer Science Department El Paso TX 79968-0514 United States Kyung Hee University Department of Applied Mathematics Yongin 446-701 Korea Republic of Arizona State University Mathematical Computational and Modeling Sciences Center Tempe AZ 85287 United States

ISBN: (纸本)9783319015675

We formulated a discrete time model in order to study optimal control strategies for a single influenza outbreak. In our model, we divided the population into four classes: susceptible, infectious, treated, and recovered individuals. The total population was divided into subgroups according to activity or susceptibility levels. The goal was to determine how treatment doses should be distributed in each group in order to reduce the final epidemic size. The case of limited resources is considered by including an isoperimetric constraint. We found that the use of antiviral treatment resulted in reductions in the cumulative number of infected individuals. We proposed to solve the problem by using the primal-dual interior-point method that enforces epidemiological constraints explicitly. © Springer International Publishing Switzerland 2014.

关键词： Optimization

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Effect of filling-factor and angle of incident on transmittance of a dielectric slab waveguide with metallic grating

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AIP Conference Proceedings 2015年第1期1656卷

作者： T. P. Negara L. Yuliawati A. D. Garnadi S. Nurdiati H. Alatas 1)Research Cluster for Dynamics and Modeling of Complex Systems Faculty of Mathematics and Natural Sciences Bogor Agricultural University Jl. Meranti Kampus IPB Darmaga Bogor 16680 Indonesia 2)Department of Computer Science Pakuan University Bogor Indonesia 3)Computational Mathematics Division Department of Mathematics Bogor Agricultural University Jl. Meranti Kampus IPB Darmaga Bogor 16680 Indonesia 4)Theoretical Physics Division Department of Physics Bogor Agricultural University Jl. Meranti Kampus IPB Darmaga Bogor 16680 Indonesia

The effect of filling factor on the transmittance characteristics of a slab waveguide with deposited metallic grating on its top is investigated by means of finite difference time domain method under uniaxial perfectly matched layer boundary condition. The system is assumed to be illuminated by a TM electromagnetic waves with oblique incidence. We studied the device transmittance for various angle of incident, while for the associated dielectric section in the grating we consider two different refractive indices. The result shows that the grating filling factor affects the device performance significantly. It is found that for certain values of filling factor and angle of incident, the difference of transmission for those two cases can be relatively large. We show this remarkable behavior is related to the surface plasmons interaction in the non-metallic section of the grating.

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Perturbed Solving Method for Interdecadal Sea-air Oscillator Model

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Chinese Geographical Science 2012年第1期22卷 42-47页

作者： MO Jiaqi LIN Yihua LIN Wantao CHEN Lihua Department of Mathematics Anhui Normal University Wuhu 241003 China Division of Computational Science E-Institutes of Shanghai Universities at Shanghai Jiaotong University Shanghai 200240 China State Key Laboratory of Numerical Modeling for Atmospheric Sciencens and Geophysical Fluid Dynamic Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Department of Mathematics and Computer Science Fuqing Branch of Fujian Normal University Fuqing 350300 China

A coupled system of the interdecadal sea-air oscillator model is studied. The E1 Nifio-southem oscillation （ENSO） atmospheric physics oscillation is an abnormal phenomenon involved in the tropical Pacific ocean-atmosphere interactions. The oscillator model is involved with the variations of both the eastern and western Pacific anomaly pat- terns. This paper proposes an ENSO atmospheric physics model using a method of the perturbation theory. The aim is to create an asymptotic solving method for the ENSO model. Employing the perturbed method, the asymptotic solution of corresponding problem is obtained, and the asymptotic behaviour of the solution is studied. Thus we can obtain the prognoses of the sea surface temperature anomaly and related physical quantities.

关键词： nonlinear equation perturbation E1 Nifio-southern oscillator model interdecadal sea-air oscillator

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Solving satisfiability in fuzzy logics with evolution strategies

Solving satisfiability in fuzzy logics with evolution strate...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Tim Brys Yann-Michaël De Hauwere Martine De Cock Ann Nowé Computational Modeling Laboratory Vrije Universiteit Brussel Brussels Belgium Department of Applied Mathematics and Computer Science Universiteit Gent Gent Belgium

Satisfiability in propositional logic is well researched and many approaches to checking and solving exist. In infinite-valued or fuzzy logics, however, there have only recently been attempts at developing methods for solving satisfiability. In this paper, we propose a new incomplete solver, based on a class of continuous optimization algorithms called evolution strategies. We show experimentally that our method is an important contribution to the state of the art in incomplete fuzzy-SAT solvers.

关键词： Sociology Covariance matrix Linear programming Fuzzy logic Benchmark testing Cognition

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A parallel accelerated adaptive mesh algorithm for the solution of electrical models of the heart

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International Journal of High Performance Systems Architecture 2012年第2期4卷 89-100页

作者： Oliveira, Rafael Sachetto Rocha, Bernardo M. Burgarelli, Denise Meira Jr., Wagner Dos Santos, Rodrigo Weber Department of Computer Science Federal University of São João de Rei Av. Visconde do Rio Preto s/n Col. do Bengo São João del-Rei MG 36301-360 Brazil Department of Computer Science Federal University of Minas Gerais Av. Antônio Carlos 6627 Pampulha Belo Horizonte MG 31270-010 Brazil National Laboratory for Scientific Computing Avenida Getúlio Vargas 333 Petrópolis RJ 25651-076 Brazil Department of Computer Science Federal University of Juiz de Fora Campus Universitário Rua José Kelmer S/n Bairro São Pedro Juiz de Fora MG 36036-330 Brazil Department of Mathematics Federal University of Minas Gerais Av. Antônio Carlos 6627 Pampulha Belo Horizonte MG 31270-010 Brazil Department of Computer Science e Computational Modeling Program Federal University of Juiz de Fora Campus Universitário Rua José Kelmer S/n Bairro São Pedro Juiz de Fora MG 36036-330 Brazil

computer models have become valuable tools for the study and comprehension of the complex phenomena of cardiac electrophysiology. However, the high complexity of the biophysical processes translates into complex mathematical and computational models. In this paper, we evaluate a parallel numerical algorithm based on mesh adaptivity and finite volume method aiming to accelerate these simulations. This is a very attractive approach since the spreading electrical wavefront corresponds only to a small fraction of the cardiac tissue. Usually, the numerical solution of the partial differential equations that model the phenomenon requires very fine spatial discretisation to follow the wavefront, which is approximately 0.2 mm. The use of uniform meshes leads to high computational cost as it requires a large number of mesh points. In this sense, the tests reported in this work show that simulations of two-dimensional models of cardiac tissue have been accelerated by more than 340 times using the adaptive mesh algorithm and parallel computing, with no significant loss in accuracy. Copyright © 2012 Inderscience Enterprises Ltd.

关键词： Wavefronts

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Predicting Parameter Sweep Jobs: From Simulation to Grid Implementation

Predicting Parameter Sweep Jobs: From Simulation to Grid Imp...

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International Conference on Complex, Intelligent and Software Intensive Systems, CISIS

作者： Peter Hellinckx Sam Verboven Frans Arickx Jan Broeckhove Research Group Computational Modeling and Programming Department of Mathematics and Computer Sciences University of Antwerp Antwerp Belgium

ISBN: (纸本)9781424435692

Efficiently using the computational power made available through desktop grids based distributed systems is a complicated and many-sided problem, caused by the intermittent resource availability. In this paper a novel solution is presented for predicting the runtimes of parameter sweep jobs. These jobs are characterized by their lack of inter-dependence and suitability for runtime prediction by modeling. This makes them ideal candidates for deployment on volatile grid configurations using prediction based techniques. The parameter sweep prediction framework used to make the predictions is referred to as GIPSy (grid information prediction system). Previous research involving GIPSy has focused on results obtained during simulation were it is necessary to make some basic assumptions. By combining GIPSy with PGS (prediction based grid scheduling), an actual grid implementation, real results can be obtained. A detailed comparison between the expected results, based on simulation analysis, and the final results is given. Discrepancies are highlighted and possible causes are identified, solutions are proposed and implemented. By comparing the results for different model building configurations an optimal configuration is found that produces reliable result independent of the chosen job type. Results are presented for a quantum physics problem and two simulated workloads represented by sleep jobs.

关键词： Predictive models Availability Runtime Scheduling computational modeling Grid computing Distributed computing Workstations Testing computational intelligence

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An information theoretic framework for eukaryotic gradient sensing 19

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20th Annual Conference on Neural Information Processing Systems, NIPS 2006

作者： Kimmel, Joseph M. Salter, Richard M. Thomas, Peter J. Computer Science Program Oberlin College Oberlin OH 44074 United States Department of Mathematics Biology and Cognitive Science Case Western Reserve University Cleveland OH 44106 United States Computational Neuroscience Graduate Program University of Chicago United States Center for Computation and Modeling United States

ISBN: (纸本)9780262195683

Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, there have been few attempts to analyze chemical signaling systems with the quantitative tools of information theory. Gradient sensing in the social amoeba Dictyostelium discoideum is a well characterized signal transduction system in which a cell estimates the direction of a source of diffusing chemoattractant molecules based on the spatiotemporal sequence of ligand-receptor binding events at the cell membrane. Using Monte Carlo techniques (MCell) we construct a simulation in which a collection of individual ligand particles undergoing Brownian diffusion in a three-dimensional volume interact with receptors on the surface of a static amoeboid cell. Adapting a method for estimation of spike train entropies described by Victor (originally due to Kozachenko and Leonenko), we estimate lower bounds on the mutual information between the transmitted signal (direction of ligand source) and the received signal (spatiotemporal pattern of receptor binding/unbinding events). Hence we provide a quantitative framework for addressing the question: how much could the cell know, and when could it know it? We show that the time course of the mutual information between the cell's surface receptors and the (unknown) gradient direction is consistent with experimentally measured cellular response times. We find that the acquisition of directional information depends strongly on the time constant at which the intracellular response is filtered.

关键词： Ligands

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