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ANNA '18;Advances in Neural Networks and Applications 2018

作者： Simeon Ribagin Tania Pencheva Anthony Shannon Department of Bioinformatics and Mathematical Modelling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Department of QSAR and Molecular Modeling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Warrane College The University of New South Wales

ISBN: (纸本)9783800747566

Surface Electromyography (sEMG) signals have been increasingly used in many applications, including biomedical, neuroprosthetic limbs, orthotic or rehabilitation devices, human machine interactions etc. In order to use such signals for the control purposes, a certain processing algorithm has to be performed. This paper presents a novel approach for sEMG data processing with the usage of generalized nets theory. We propose an abstract model representing the sEMG data processing, which can be used in the control frameworks of active elbow orthosis devices.

关键词： Standing Orders SEMA5B gene Surface Electromyography Automatic data processing data processing Orthotic Devices network model Elbow signals

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Correction to: Meeting report from the fourth meeting of the Computational modeling in Biology Network (COMBINE)

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Standards in genomic sciences 2018年第1期13卷 17页

作者： Dagmar Waltemath Frank T Bergmann Claudine Chaouiya Tobias Czauderna Padraig Gleeson Carole Goble Martin Golebiewski Michael Hucka Nick Juty Olga Krebs Nicolas Le Novère Huaiyu Mi Ion I Moraru Chris J Myers David Nickerson Brett G Olivier Nicolas Rodriguez Falk Schreiber Lucian Smith Fengkai Zhang Eric Bonnet 1Department of Systems Biology and Bioinformatics University of Rostock Rostock Germany. 2Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA. 4Instituto Gulbenkian de Ciência - IGC Rua da Quinta Grande Oeiras Portugal. 3IPK Gatersleben Gatersleben Germany. 5Department of Neuroscience Physiology and Pharmacology University College London London UK. 6School of Computer Science The University of Manchester Manchester UK. 7Heidelberg Institute for Theoretical Studies Heidelberg Germany. 8EMBL-European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton Cambridge UK. 14The Babraham Institute Babraham Research Campus Cambridge UK. 9Department of preventive medicine Keck School of Medicine University of Southern California Los Angeles CA USA. 10Center for Cell Analysis and Modeling University of Connecticut Health Center Farmington CT USA. 11Department of Electrical and Computer Engineering University of Utah Salt Lake City USA. 12Auckland Bioengineering Institute University of Auckland Auckland New Zealand. 13Systems Bioinformatics VU University Amsterdam Amsterdam The Netherlands. 15Martin Luther University Halle-Wittenberg Halle Germany. 16Monash University Melbourne Australia. Computational Biology Unit Laboratory of Systems Biology National Institute of Allergy and Infectious Diseases NIH Bethesda MD USA. 18Institut Curie Paris France. INSERM U900 75248 Paris France. 20Mines ParisTech 77300 Fontainebleau Paris France.

[This corrects the article DOI: 10.4056/sigs.5279417.].

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Creation and analysis of biochemical constraint-based models: The COBRA Toolbox v3.0

arXiv

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arXiv 2017年

作者： Heirendt, Laurent Arreckx, Sylvain Pfau, Thomas Mendoza, Sebastián N. Richelle, Anne Heinken, Almut Haraldsdóttir, Hulda S. Wachowiak, Jacek Keating, Sarah M. Vlasov, Vanja Magnusdóttir, Stefania Ng, Chiam Yu Preciat, German Žagare, Alise Chan, Siu H.J. Aurich, Maike K. Clancy, Catherine M. Modamio, Jennifer Sauls, John T. Noronha, Alberto Bordbar, Aarash Cousins, Benjamin El Assal, Diana C. Valcarcel, Luis V. Apaolaza, Iñigo Ghaderi, Susan Ahookhosh, Masoud Guebila, Marouen Ben Kostromins, Andrejs Sompairac, Nicolas Le, Hoai M. Ma, Ding Sun, Yuekai Wang, Lin Yurkovich, James T. Oliveira, Miguel A.P. Vuong, Phan T. El Assal, Lemmer P. Kuperstein, Inna Zinovyev, Andrei Scott Hinton, H. Bryant, William A. Aragón Artacho, Francisco J. Planes, Francisco J. Stalidzans, Egils Maass, Alejandro Vempala, Santosh Hucka, Michael Saunders, Michael A. Maranas, Costas D. Lewis, Nathan E. Sauter, Thomas Palsson, Bernhard Ø. Thiele, Ines Fleming, Ronan M.T. Luxembourg Centre for Systems Biomedicine University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg Life Sciences Research Unit University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg University of Chile Blanco Encalada 2085 Santiago Chile Department of Pediatrics University of California San Diego School of Medicine San DiegoCA92093 United States Hinxton CambridgeCB10 1SD United Kingdom Department of Chemical Engineering Pennsylvania State University University University ParkPA16802 United States Department of Physics University of California San Diego 9500 Gilman Dr. San DiegoCA92093 United States Bioinformatics and Systems Biology Program University of California San Diego San DiegoCA United States Sinopia Biosciences San DiegoCA United States School of Computer Science Algorithms and Randomness Center Georgia Institute of Technology AtlantaGA United States Biomedical Engineering and Sciences Department TECNUN University of Navarra Paseo de Manuel Lardizabal 13 San Sebastian20018 Spain Institute of Microbiology and Biotechnology University of Latvia Jelgavas iela 1 RigaLV-1004 Latvia Department of Management Science and Engineering Stanford University StanfordCA94305-4026 United States Bioengineering Department University of California San Diego San DiegoCA United States Utah State University Research Foundation 1695 North Research Park Way North LoganUT84341 United States Centre for Integrative Systems Biology and Bioinformatics Department of Life Sciences Imperial College London London United Kingdom Department of Mathematics University of Alicante Spain California Institute of Technology Computing and Mathematical Sciences MC 305-16 1200 E. California Blvd. PasadenaCA91125 United States Mathomics Center for Mathematical Modeling University of Chile Beauchef 851 Santiago Chile Novo Nordisk Foundation Center for Biosustainability University of California San Diego San DiegoCA92093 Uni

COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Data integration

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Pressing topics in the Belgian water sector anno 2015

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Sustainability of Water Quality and Ecology 2016年 7卷 32-36页

作者： De Mulder, C. Van Hoey, S. Van Hulle, S. Agathos, S.N. Cauwenberg, P. Mergen, P. Seuntjens, P. Smets, I. De Gueldre, G. Mouton, A. Schowanek, D. Meesschaert, B. Verstraete, W. Nopens, I. BIOMATH Department of Mathematical Modelling Statistics and Bioinformatics Faculty of Bioscience Engineering Ghent University Coupure Links 653 Gent 9000 Belgium LIWET Department of Industrial Biological Sciences Ghent University Graaf Karel de Goedelaan 5 Kortrijk 8500 Belgium Laboratory of Bioengineering Earth and Life Institute Université Catholique de Louvain Louvain-la-Neuve 1348 Belgium Unit Environmental Modeling Flemish Institute for Technological Research (VITO) Boeretang 200 Mol 2400 Belgium Royal Museum for Central Africa Leuvensesteenweg 13 Tervuren 3080 Belgium Botanic Garden Meise Bouchout Domain Nieuwelaan 38 Meise 1860 Belgium Department of Soil Management Faculty of Bioscience Engineering Ghent University Coupure Links 653 Gent 9000 Belgium Department of Bioscience Engineering University of Antwerp Groenenborgerlaan 171 Antwerpen 2000 Belgium CREaS Department of Chemical Engineering KU Leuven Celestijnenlaan 200F Leuven 3001 Belgium Aquafin NV Dijkstraat 8 Aartselaar 2630 Belgium Technology Campus Gent Odisee Hogeschool Gebroeders De Smetstraat 1 Gent 9000 Belgium Environmental Stewardship and Sustainability - Brussels Innovation Center Procter and Gamble Temselaan 100 Strombeek-Bever 1853 Belgium Cluster for Bioengineering Technology Department of Microbial and Molecular Systems KU Leuven Technology Campus Ostend Zeedijk 101 Oostende B-8400 Belgium LabMET Department of Biochemical and Microbial Technology Faculty of Bioscience Engineering Ghent University Coupure Links 653 Gent 9000 Belgium

Today's water sector is governed by some hot topics, and this is no different in Belgium. As for the International Water Association (IWA), the goal of its Belgian division (B-IWA) is to gather different stakeholders, i.e. academics, policy makers and people from industry active in the (Belgian) water sector and trigger the debate. In May 2015, a first Nocturnal was organised to accomplish just this. Seven hot water topics, proposed by participants at the time of their online registration, were addressed in rotating round table discussions. These topics included resource recovery, micropollutants, water scarcity, hydroinformatics, integrated water management and modeling, technology vs. legislation and Computational Fluid Dynamics in water applications. The lively discussions led to the idea of this short contribution describing the outcomes of these round table discussions, along with some additional research on the topics. Main conclusions include the need for education (both of scholars and young professionals), inter-domain communication and the growing importance of IT in the water sector. © 2016 Elsevier B.V.

关键词： Education Industry Informatics Legislation Water sector

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Generalized antisymmetric filters for edge detection

Generalized antisymmetric filters for edge detection

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International Conference of Soft Computing and Pattern Recognition (SOCPAR)

作者： Nicolás Madrid Carlos Lopez-Molina Bernard De Baets Institute for Research and Applications of Fuzzy Modeling University of Ostrava Ostrava Czech Republic Dpto. Automatica y Computacion Universidad Publica de Navarra Pamplona Spain Dept. of Mathematical Modeling Statistics and Bioinformatics Ghent University Gent Belgium

A large number of filters has been proposed to compute local gradients in grayscale images, usually having as goal the adequate characterization of edges. A significant portion of such filters are antisymmetric with respect to the origin. In this work we propose to generalize those filters by incorporating an explicit evaluation of the tonal difference. More specifically, we propose to apply restricted dissimilarity functions to appropriately measure the tonal differences. We present the mathematical developments, as well as quantitative experiments that indicate that our proposal offers a clear option to improve the performance of classical edge detection filters.

关键词： Image edge detection Convolution Proposals Feature extraction Computational modeling Approximation methods Pattern recognition

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Concurrent algorithm for learning of neural networks

Concurrent algorithm for learning of neural networks

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2012 6th IEEE International Conference Intelligent Systems, IS 2012

作者： Antonov, Anton Hadjitodorov, Stefan Bioinformatics and Mathematical Modeling IBPhBME-Bulgarian Academy of Sciences Sofia Bulgaria

The purpose of the paper is to present an algorithm for concurrent processing on multi-layer neural networks and its advantages in the context of development of parallel computing systems and clouds. © 2012 IEEE.

ISBN: (纸本)9781467327824

关键词： Network layers

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Label ranking with partial abstention based on thresholded probabilistic models

Label ranking with partial abstention based on thresholded p...

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26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012

作者： Cheng, Weiwei Hüllermeier, Eyke Waegeman, Willem Welker, Volkmar Mathematics and Computer Science Philipps-Universität Marburg Marburg Germany Mathematical Modeling Statistics and Bioinformatics Ghent University Ghent Belgium

ISBN: (纸本)9781627480031

Several machine learning methods allow for abstaining from uncertain predictions. While being common for settings like conventional classification, abstention has been studied much less in learning to rank. We address abstention for the label ranking setting, allowing the learner to declare certain pairs of labels as being incomparable and, thus, to predict partial instead of total orders. In our method, such predictions are produced via thresholding the probabilities of pairwise preferences between labels, as induced by a predicted probability distribution on the set of all rankings. We formally analyze this approach for the Mallows and the Plackett-Luce model, showing that it produces proper partial orders as predictions and characterizing the expressiveness of the induced class of partial orders. These theoretical results are complemented by experiments demonstrating the practical usefulness of the approach.

关键词： Forecasting

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Concurrent Algorithm for Learning of Neural Networks

Concurrent Algorithm for Learning of Neural Networks

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IEEE International Conference Intelligent Systems

作者： Anton Antonov Stefan Hadjitodorov Bioinformatics and Mathematical Modeling IBPhBME - Bulgarian Academy of Sciences Sofia Bulgaria

the purpose of the paper is to present an algorithm for concurrent processing on multi-layer neural networks and its advantages in the context of development of parallel computing systems and clouds.

ISBN: (纸本)9781467322768

the purpose of the paper is to present an algorithm for concurrent processing on multi-layer neural networks and its advantages in the context of development of parallel computing systems and clouds.

关键词： neural networks concurrent algorithm generalized nets Neural network PARALLEL PROCESSING (COMPUTERS) Parallel algorithms Clouds Multilayer neural networks Learning parallel computing system

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Label ranking with partial abstention based on thresholded probabilistic models 12

Label ranking with partial abstention based on thresholded p...

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Proceedings of the 26th International Conference on Neural Information Processing Systems - Volume 2

作者： Weiwei Cheng Eyke Hüllermeier Willem Waegeman Volkmar Welker Mathematics and Computer Science Philipps-Universität Marburg Marburg Germany Mathematical Modeling Statistics and Bioinformatics Ghent University Ghent Belgium

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Application of genetic algorithm to tuning a PID controller for glucose concentration control

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WSEAS Transactions on Systems 2012年第7期11卷 223-233页

作者： Slavov, Tsonio Roeva, Olympia Department of Automatics and Systems Engineering Technical University of Sofia 8 Kliment Ohridski Blvd. 1756 Sofia Bulgaria Department of Bioinformatics and Mathematical Modeling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences 105 Acad G. Bonchev Str. 1113 Sofia Bulgaria

The paper presents a feedforward feedback (PID) controller designed for control of glucose concentration during the E. coli fed-batch cultivation process. The controller is used to control the feed rate and to maintain glucose concentration at a desired set point. Taking into account the measurement system particularities, the modified process model is proposed. An equation for correction of the measured glucose based on Kalman filter estimates of biomass concentration and bacteria growth rate is suggested. To achieve good closed-loop system performance genetic algorithm tuning of the PID controller is used. As a result, the optimal PID controller settings are obtained. For a short time the controller sets the control variable and maintains it at the desired set point during the process. Based on the proposed model correction, the estimations of the process parameters are brought closer to the real values. Tuning of the controller on the basis of a genetic algorithm leads to higher level of accuracy and efficiency of the system performance.

关键词： Genetic algorithms

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