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154 results on '"Westra, Ronald"'

1. A quantum algorithm for track reconstruction in the LHCb vertex detector

Author

Nicotra, Davide, Martinez, Miriam Lucio, de Vries, Jacco Andreas, Merk, Marcel, Driessens, Kurt, Westra, Ronald Leonard, Dibenedetto, Domenica, and Pérez, Daniel Hugo Cámpora

Subjects
Quantum Physics, Computer Science - Emerging Technologies, High Energy Physics - Experiment
Abstract

High-energy physics is facing increasingly computational challenges in real-time event reconstruction for the near-future high-luminosity era. Using the LHCb vertex detector as a use-case, we explore a new algorithm for particle track reconstruction based on the minimisation of an Ising-like Hamiltonian with a linear algebra approach. The use of a classical matrix inversion technique results in tracking performance similar to the current state-of-the-art but with worse scaling complexity in time. To solve this problem, we also present an implementation as quantum algorithm, using the Harrow-Hassadim-Lloyd (HHL) algorithm: this approach can potentially provide an exponential speedup as a function of the number of input hits over its classical counterpart, in spite of limitations due to the well-known HHL Hamiltonian simulation and readout problems. The findings presented in this paper shed light on the potential of leveraging quantum computing for real-time particle track reconstruction in high-energy physics., Comment: 23 pages, 10 figures

Published
2023

2. Hybrid Quantum Singular Spectrum Decomposition for Time Series Analysis

Author

Postema, Jasper Johannes, Bonizzi, Pietro, Koekoek, Gideon, Westra, Ronald L., and Kokkelmans, Servaas J. J. M. F.

Subjects
Quantum Physics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Classical data analysis requires computational efforts that become intractable in the age of Big Data. An essential task in time series analysis is the extraction of physically meaningful information from a noisy time series. One algorithm devised for this very purpose is singular spectrum decomposition (SSD), an adaptive method that allows for the extraction of narrow-banded components from non-stationary and non-linear time series. The main computational bottleneck of this algorithm is the singular value decomposition (SVD). Quantum computing could facilitate a speedup in this domain through superior scaling laws. We propose quantum SSD by assigning the SVD subroutine to a quantum computer. The viability for implementation and performance of this hybrid algorithm on a near term hybrid quantum computer is investigated. In this work we show that by employing randomised SVD, we can impose a qubit limit on one of the circuits to improve scalibility. Using this, we efficiently perform quantum SSD on simulations of local field potentials recorded in brain tissue, as well as GW150914, the first detected gravitational wave event., Comment: 18 pages, 6 figures

Published
2022
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3. Searching for ring-like structures in the Cosmic Microwave Background

Author

Lopez, Melissa, Bonizzi, Pietro, Driessens, Kurt, Koekoek, Gideon, de Vries, Jacco, and Westra, Ronald

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

In this research, we present an alternative methodology to search for ring-like structures in the sky with unusually large temperature gradients, namely Hawking points (HP), in the Cosmic Microwave Background (CMB), which are possible observational effects associated with Conformal Cyclic Cosmology (CCC). To assess the performance of our method, we constructed an artificial data set of HP, according to CCC, and we were able to retrieve $95 \%$ of ring-like anomalies from it. Furthermore, we scanned the \textit{Planck} CMB sky map and compared it to simulations according to $\Lambda CDM$, where we applied robust statistical tests to assess the existence of HP. Even though no significant ring-like structures were observed, we report the largest excess of HP candidates found at $\alpha = $1\% significance level for the analyzed sky maps (CMB at 70GHz, SEVEM, SMICA, and Commander-Ruler), and we stress the need to continue the theoretical and experimental research in this direction., Comment: 9 pages, 5 figures, 1 table, 1 algorithm

Published
2021
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4. Effects of Synaptic and Myelin Plasticity on Learning in a Network of Kuramoto Phase Oscillators

Author

Karimian, Maryam, Dibenedetto, Domenica, Moerel, Michelle, Burwick, Thomas, Westra, Ronald, De Weerd, Peter, and Senden, Mario

Subjects
Nonlinear Sciences - Adaptation and Self-Organizing Systems, 34C15
Abstract

Models of learning typically focus on synaptic plasticity. However, learning is the result of both synaptic and myelin plasticity. Specifically, synaptic changes often co-occur and interact with myelin changes, leading to complex dynamic interactions between these processes. Here, we investigate the implications of these interactions for the coupling behavior of a system of Kuramoto oscillators. To that end, we construct a fully connected, one-dimensional ring network of phase oscillators whose coupling strength (reflecting synaptic strength) as well as conduction velocity (reflecting myelination) are each regulated by a Hebbian learning rule. We evaluate the behavior of the system in terms of structural (pairwise connection strength and conduction velocity) and functional connectivity (local and global synchronization behavior). We find that for conditions in which a system limited to synaptic plasticity develops two distinct clusters both structurally and functionally, additional adaptive myelination allows for functional communication across these structural clusters. Hence, dynamic conduction velocity permits the functional integration of structurally segregated clusters. Our results confirm that network states following learning may be different when myelin plasticity is considered in addition to synaptic plasticity, pointing towards the relevance of integrating both factors in computational models of learning., Comment: 39 pages, 15 figures This work is submitted in Chaos: An Interdisciplinary Journal of Nonlinear Science

Published
2019
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8. Identification of Piecewise Linear Models of Complex Dynamical Systems

Author

Westra, Ronald L., Petreczky, Mihály, and Peeters, Ralf L. M.

Subjects
Mathematics - Optimization and Control, Computer Science - Systems and Control, 93B15, 93B20, 93B25, 93C99
Abstract

The paper addresses the realization and identification problem or a subclass of piecewise-affine hybrid systems. The paper provides necessary and sufficient conditions for existence of a realization, a characterization of minimality, and an identification algorithm for this subclass of hybrid systems. The considered system class and the identification problem are motivated by applications in systems biology.

Published
2011

11. The Identification of Dynamic Gene-Protein Networks

Author

Westra, Ronald L., Hollanders, Goele, Bex, Geert Jan, Gyssens, Marc, Tuyls, Karl, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Tuyls, Karl, editor, Westra, Ronald, editor, Saeys, Yvan, editor, and Nowé, Ann, editor

Published
2007
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14. Hybrid Quantum Singular Spectrum Decomposition for Time Series Analysis

Author

Jasper Postema, Pietro Bonizzi, Gideon Koekoek, Westra, Ronald L., Servaas Kokkelmans, Coherence and Quantum Technology, and Center for Quantum Materials and Technology Eindhoven

Subjects
Quantum Physics, quant-ph, FOS: Physical sciences, Quantum Physics (quant-ph), Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM)
Abstract

Classical data analysis requires computational efforts that become intractable in the age of Big Data. An essential task in time series analysis is the extraction of physically meaningful information from a noisy time series. One algorithm devised for this very purpose is singular spectrum decomposition (SSD), an adaptive method that allows for the extraction of narrow-banded components from non-stationary and non-linear time series. The main computational bottleneck of this algorithm is the singular value decomposition (SVD). Quantum computing could facilitate a speedup in this domain through superior scaling laws. We propose quantum SSD by assigning the SVD subroutine to a quantum computer. The viability for implementation and performance of this hybrid algorithm on a near term hybrid quantum computer is investigated. In this work we show that by employing randomised SVD, we can impose a qubit limit on one of the circuits to improve scalibility. Using this, we efficiently perform quantum SSD on simulations of local field potentials recorded in brain tissue, as well as GW150914, the first detected gravitational wave event., 18 pages, 6 figures

Published
2022

15. On Phase Transitions in Learning Sparse Networks

Author

Hollanders, Goele, Bex, Geert Jan, Gyssens, Marc, Westra, Ronald L., Tuyls, Karl, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Kok, Joost N., editor, Koronacki, Jacek, editor, Mantaras, Raomon Lopez de, editor, Matwin, Stan, editor, Mladenič, Dunja, editor, and Skowron, Andrzej, editor

Published
2007
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17. Additional file 1 of Hydropathicity-based prediction of pain-causing NaV1.7 variants

Author

Makros N. Xenakis, Kapetis, Dimos, Yang, Yang, Gerrits, Monique M., Heijman, Jordi, Waxman, Stephen G., Lauria, Giuseppe, Faber, Catharina G., Westra, Ronald L., Lindsey, Patrick J., and Smeets, Hubert J.

Subjects
InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, ComputingMilieux_COMPUTERSANDEDUCATION, Data_FILES, ComputerApplications_COMPUTERSINOTHERSYSTEMS
Abstract

Additional file 1: Supplementary information.

Published
2021
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19. Hydropathicity-Based Prediction of Pain-Causing NaV1.7 Variants

Author

Xenakis, Markos, primary, Kapetis, Dimos, additional, Yang, Yang, additional, Gerrits, Monique, additional, Heijman, Jordi, additional, Waxman, Stephen, additional, Lauria, Giuseppe, additional, Faber, Catharina, additional, Westra, Ronald, additional, Lindsey, Patrick, additional, and Smeets, Hubert, additional

Published
2021
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26. Resonance-driven ion transport and selectivity in prokaryotic ion channels

Author

Westra, Ronald and Westra, Ronald

Abstract

Ion channels exhibit a remarkably high accuracy in selecting uniquely its associated type of ion. The mechanisms behind ion selectivity are not well understood. Current explanations build mainly on molecular biology and bioinformatics. Here we propose a simple physical model for ion selectivity based on the driven damped harmonic oscillator (DDHO). The driving force for this oscillator is provided by self-organizing harmonic turbulent structures in the dehydrating ionic flow through the ion channel, namely, oscillating pressure waves in one dimension, and toroidal vortices in two and three dimensions. Density fluctuations caused by these turbulences efficiently transmit their energy to aqua ions that resonate with the driving frequency. Consequently, these release their hydration shell and exit the ion channel as free ions. Existing modeling frameworks do not express the required complex spatiotemporal dynamics, hence we introduce a macroscopic continuum model for ionic dehydration and transport, based on the hydrodynamics of a dissipative ionic flow through an ion channel, subject to electrostatic and amphiphilic interactions. This model combines three classical physical fields: Navier-Stokes equations from hydrodynamics, Gauss's law from Maxwell theory, and the convection-diffusion equation from continuum physics. Numerical experiments with mixtures of chemical species of ions in various degrees of hydration indeed reveal the emergence of strong oscillations in the ionic flow that are instrumental in the efficient dehydration and cause a strong ionic jet into the cell. As such, they provide a powerful engine for the DDHO mechanism. Theoretical predictions of the modeling framework match significantly with empirical patch-clamp data. The DDHO standard response curve defines a unique resonance frequency that depends on the mass and charge of the ion. In this way, the driving oscillations act as a selection mechanism that filters out one specific ion. Application

Published
2019

27. Effects of Hebbian learning on networks of Kuramoto phase oscillators with time delay

Author

Karimian, Maryam, Dibenedetto, Menica, Moerel, Michelle, De Weerd, Peter, Burwick, Thomas, Westra, Ronald, DKE Scientific staff, RS: FSE MaCSBio, RS: FSE DACS BMI, RS: FPN MaCSBio, Perception, RS: FPN CN 3, Maastricht Centre for Systems Biology, and RS: FSE DACS

Subjects
Quantitative Biology::Neurons and Cognition
Abstract

Neuronal oscillations are crucial for various cognitive functions, including learning. Among neuronal populations, patterns of synchronization can drive connectivity changes, in turn modifying oscillations and synchronization. To study changes in oscillation patterns with learning, we modeled brain processing using a directed random network of phase-coupled oscillators interacting according to the Kuramoto model

Published
2017

28. Additional file 6: Figure S2. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

Degree variation (â D) in NaV1.7 mutations compared to WT. (DOCX 1691Â kb)

Published
2017
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29. Additional file 5: S2. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

Text. Pairwise sequence alignment between human SCN9A and homologous genes. (DOCX 34Â kb)

Published
2017
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30. Additional file 16: Figure S6. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

Structural modelling variants and their interatomic bonds of I848T and N395K. (DOCX 747Â kb)

Published
2017
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31. Additional file 7: Figure S3. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

Clustering coefficient variation (â CC ct ) in NaV1.7 mutations compared to WT. (DOCX 2798Â kb)

Published
2017
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32. Additional file 2: Table S1. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

NaV1.7 mutations associated to IEM, SFN and PEPD. (DOCX 50Â kb)

Published
2017
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34. Additional file 1: S1. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

Text. Phylogenenetic tree of human SCN9A and homologous genes. (DOCX 35Â kb)

Published
2017
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35. Additional file 8: Figure S4. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

Closeness Centrality variation (â C ct ) in NaV1.7 mutations compared to WT.A (DOCX 2801Â kb)

Published
2017
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36. Additional file 9: Figure S5. of Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Author

Kapetis, Dimos, Sassone, Jenny, Yang, Yang, Galbardi, Barbara, Xenakis, Markos, Westra, Ronald, Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina, Gerrits, Monique, Merkies, Ingemar, Dib-Hajj, Sulayman, Mantegazza, Massimo, Waxman, Stephen, and Lauria, Giuseppe

Abstract

Eccentricity centrality variation (â E ct ) in NaV1.7 mutations compared to WT. (DOCX 2709Â kb)

Published
2017
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37. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

Author

Newton, Adam J H, Seidenstein, Alexandra H, McDougal, Robert A, Cervera, Alberto, Huguet, Gemma, Seara, Tere, Haimerl, Caroline, Garcia, David, Torcini, Alessandro, Cossart, Rosa, Malvache, Arnaud, Skiker, Kaoutar, Maouene, Mounir, Ragognetti, Gianmarco, Lorusso, Letizia, Viggiano, Andrea, Marcelli, Angelo, Senatore, Rosa, Parziale, Antonio, Stramaglia, S., Pellicoro, M., Angelini, L., Amico, E., Aerts, H., Cortés, J., Laureys, S., Marinazzo, D., Bassez, I., Faes, L., Almgren, Hannes, Razi, Adeel, Steen, Frederik, Krebs, Ruth, Aerts, Hannelore, Kanari, Lida, Dlotko, Pawel, Scolamiero, Martina, Levi, Ran, Shillcock, Julian, Kock, Christiaan P, Hess, Kathryn, Markram, Henry, Ly, Cheng, Marsat, Gary, Gillespie, Tom, Sandström, Malin, Abrams, Mathew, Grethe, Jeffrey S, Martone, Maryann, Gernier, Robin, Solinas, Sergio, Rössert, Christian, Haelterman, Marc, Massar, Serge, Pasquale, Valentina, Pastore, Vito P, Martinoia, Sergio, Massobrio, Paolo, Capone, Cristiano, Colet, Núria, Vives, Maria V, Mattia, Maurizio, Almasi, Ali, Cloherty, Shaun L, Grayden, David B, Wong, Yan T, Ibbotson, Michael R, Meffin, Hamish, Prince, Luke Y, Atanasova, Krasimira, Mellor, Jack R, Mazzoni, Alberto, Rosa, Manuela, Carpaneto, Jacopo, Romito, Luigi M, Priori, Alberto, Micera, Silvestro, Migliore, Rosanna, Lupascu, Carmen A, Franchina, Francesco, Bologna, Luca L, Romani, Armando, Saray, Sára, Geit, Werner, Káli, Szabolcs, Thomson, Alex, Mercer, Audrey, Lange, Sigrun, Falck, Joanne, Muller, Eilif, Schürmann, Felix, Todorov, Dmitrii, Capps, Robert, Barnett, William, Molkov, Yaroslav, Devalle, Federico, Pazó, Diego, Montbrió, Ernest, Mochol, Gabriela, Azab, Habiba, Hayden, Benjamin Y, Bote, Rubén, Balasubramani, Pragathi P, Chakravarthy, Srinivasa V, Muddapu, Vignayanandam R, Gheorghiu, Medorian D, Mimica, Bartul, Withlock, Jonathan, Mureșan, Raul C, Zick, Jennifer L, Schultz, Kelsey, Blackman, Rachael K, Chafee, Matthew V, Netoff, Theoden I, Roberts, Nicholas, Nagaraj, Vivek, Lamperski, Andrew, Grado, Logan L, Johnson, Matthew D, Darrow, David P, Lonardoni, Davide, Amin, Hayder, Marco, Stefano, Maccione, Alessandro, Berdondini, Luca, Nieus, Thierry, Stimberg, Marcel, Goodman, Dan F M, Nowotny, Thomas, Koren, Veronika, Dragoi, Valentin, Obermayer, Klaus, Castro, Samy, Fernandez, Mariano, Deredy, Wael, Xu, Kesheng, Maidana, Jean P, Orio, Patricio, Chen, Weiliang, Hepburn, Iain, Casalegno, Francesco, Devresse, Adrien, Ovcharenko, Aleksandr, Pereira, Fernando, Delalondre, Fabien, Schutter, Erik, Bratby, Peter, Gallimore, Andrew R, Klingbeil, Guido, Zamora, Criseida, Zang, Yunliang, Crotty, Patrick, Palmerduca, Eric, Antonietti, Alberto, Casellato, Claudia, Erö, Csaba, Angelo, Egidio, Gewaltig, Marc-Oliver, Pedrocchi, Alessandra, Bytschok, Ilja, Dold, Dominik, Schemmel, Johannes, Meier, Karlheinz, Petrovici, Mihai A, Shen, Hui-An, Surace, Simone C, Pfister, Jean-Pascal, Lefebvre, Baptiste, Marre, Olivier, Yger, Pierre, Papoutsi, Athanasia, Park, Jiyoung, Ash, Ryan, Smirnakis, Stelios, Poirazi, Panayiota, Felix, Richard A, Dimitrov, Alexander G, Portfors, Christine, Daun, Silvia, Toth, Tibor I, Szmek, Joanna, Kabbani, Nadine, Blackwel, Kim T, Moezzi, Bahar, Schaworonkow, Natalie, Plogmacher, Lukas, Goldsworthy, Mitchell R, Hordacre, Brenton, McDonnell, Mark D, Iannella, Nicolangelo, Ridding, Michael C, Triesch, Jochen, Maex, Reinoud, Safaryan, Karen, Steuber, Volker, Tang, Rongxiang, Tang, Yi-Yuan, Verveyko, Darya V, Brazhe, Alexey R, Verisokin, Andrey Y, Postnov, Dmitry E, Günay, Cengiz, Panuccio, Gabriella, Giugliano, Michele, Prinz, Astrid A, Varona, Pablo, Rabinovich, Mikhail I, Denham, Jack, Ranner, Thomas, Cohen, Netta, Reva, Maria, Rebola, Nelson, Kirizs, Tekla, Nusser, Zoltan, DiGregorio, David, Mavritsaki, Eirini, Rentzelas, Panos, Ukani, Nikul H, Tomkins, Adam, Yeh, Chung-Heng, Bruning, Wesley, Fenichel, Allison L, Zhou, Yiyin, Huang, Yu-Chi, Florescu, Dorian, Ortiz, Carlos L, Richmond, Paul, Lo, Chung-Chuan, Coca, Daniel, Chiang, Ann-Shyn, Lazar, Aurel A, Creaser, Jennifer L, Lin, Congping, Ashwin, Peter, Brown, Jonathan T, Ridler, Thomas, Levenstein, Daniel, Watson, Brendon O, Buzsáki, György, Rinzel, John, Curtu, Rodica, Nguyen, Anh, Assadzadeh, Sahand, Robinson, Peter A, Leon, Paula, Forlim, Caroline G, Almeida, Lírio O B, Pinto, Reynaldo D, Rodríguez, Francisco B, Lareo, Ángel, Montero, Aaron, Mosqueiro, Thiago, Huerta, Ramon, Rodriguez, Francisco B, Changoluisa, Vinicio, Cordeiro, Vinícius L, Ceballos, César C, Kamiji, Nilton L, Roque, Antonio C, Lytton, William W, Knox, Andrew, Rosenthal, Joshua J C, Popovych, Svitlana, Liu, Liqing, Wang, Bin A, Tóth, Tibor I, Grefkes, Christian, Fink, Gereon R, Rosjat, Nils, Trujillo, Abraham, Espinal, Andres, Figueroa, Marco A, Aceves, Ivan, Gonzalez, Horacio, Zapotocky, Martin, Hoskovcová, Martina, Kopecká, Jana, Ulmanová, Olga, Růžička, Evžen, Gärtner, Matthias, Duvarci, Sevil, Roeper, Jochen, Schneider, Gaby, Albert, Stefan, Schmack, Katharina, Remme, Michiel, Schreiber, Susanne, Migliore, Michele, Antonel, Stefano M, Courcol, Jean-Denis, Çelikok, Sami U, López, Eva M, Şengör, Neslihan S, Elibol, Rahmi, Sengor, Neslihan S, Özdemir, Mustafa Y, Li, Tianyi, Arleo, Angelo, Sheynikhovich, Denis, Nakamura, Akihiro, Shimono, Masanori, Song, Youngjo, Park, Sol, Choi, Ilhwan, Jeong, Jaeseung, Shin, Hee-sup, Sadeh, Sadra, Gleeson, Padraig, Silver, R., Chatzikalymniou, Alexandra P, Skinner, Frances K, Rodriguez, Lazaro M, Sotero, Roberto C, Hertäg, Loreen, Mackwood, Owen, Sprekeler, Henning, Puhlmann, Steffen, Weber, Simon N, Higgins, David, Naumann, Laura B, Iyer, Ramakrisnan, Mihalas, Stefan, Ticcinelli, Valentina, Stankovski, Tomislav, McClintock, Peter V E, Stefanovska, Aneta, Janjić, Predrag, Solev, Dimitar, Seifert, Gerald, Kocarev, Ljupčo, Steinhäuser, Christian, Salmasi, Mehrdad, Glasauer, Stefan, Stemmler, Martin, Zhang, Danke, Zhang, Chi, Stepanyants, Armen, Goncharenko, Julia, Kros, Lieke, Davey, Neil, Zeeuw, Chris, Hoebeek, Freek, Sinha, Ankur, Adams, Roderick, Schmuker, Michael, Psarrou, Maria, Schilstra, Maria, Nielsen, Benjamin, Metzner, Christoph, Schweikard, Achim, Marttunen, Tuomo, Zurowski, Bartosz, Marinazzo, Daniele, Faes, Luca, Stramaglia, Sebastiano, Jordan, Henry O C, Stringer, Simon M, Dendek, Elżbieta, Suffczyński, Piotr, Tam, Nicoladie, Zouridakis, George, Pollonini, Luca, Asl, Mojtaba M, Valizadeh, Alireza, Tass, Peter A, Nold, Andreas, Fan, Wei, Konrad, Sara, Endle, Heiko, Vogt, Johannes, Tchumatchenko, Tatjana, Herpich, Juliane, Tetzlaff, Christian, Luboeinski, Jannik, Nachstedt, Timo, Ciba, Manuel, Bahmer, Andreas, Thielemann, Christiane, Kuebler, Eric S, Tauskela, Joseph S, Thivierge, Jean-Philippe, Bakker, Rembrandt, Amado, María, Evangelio, Marian, Clascá, Francisco, Tiesinga, Paul, Buckley, Christopher L, Toyoizumi, Taro, Dubreuil, Alexis M, Monasson, Rémi, Treves, Alessandro, Spalla, Davide, Rosay, Sophie, Kleberg, Florence I, Wong, Willy, Floriano, Bruno, Matsuo, Toshihiko, Uchida, Tetsuya, Dibenedetto, Domenica, Uludağ, Kâmil, Goodarzinick, Abdorreza, Schmidt, Maximilian, Hilgetag, Claus C, Diesmann, Markus, Albada, Sacha J, Fauth, Michael, Rossum, Mark, Sánchez, Manuel, Amaducci, Rodrigo, Muñiz, Carlos, Elices, Irene, Arroyo, David, Levi, Rafael, Cohen, Ben, Chow, Carson, Vattikuti, Shashaank, Bertolotti, Elena, Burioni, Raffaella, Volo, Matteo, Vezzani, Alessandro, Menzat, Bayar, Vogels, Tim P, Wagatsuma, Nobuhiko, Saha, Susmita, Kapoor, Reena, Kerr, Robert, Wagner, John, Molino, Luis C G, Yang, Guangyu R, Mejias, Jorge F, Wang, Xiao-Jing, Song, Hanbing, Goodliffe, Joseph, Luebke, Jennifer, Weaver, Christina M, Thomas, John, Sinha, Nishant, Shaju, Nikhita, Maszczyk, Tomasz, Jin, Jing, Cash, Sydney S, Dauwels, Justin, Westover, M., Karimian, Maryam, Moerel, Michelle, Weerd, Peter, Burwick, Thomas, Westra, Ronald L, Abeysuriya, Romesh, Hadida, Jonathan, Sotiropoulos, Stamatios, Jbabdi, Saad, Woolrich, Mark, Bensmail, Chama, Wrobel, Borys, Zhou, Xiaolong, Ji, Zilong, Liu, Xiao, Xia, Yan, Wu, Si, Wang, Xiao, Zhang, Mingsha, Ofer, Netanel, Shefi, Orit, Yaari, Gur, Carnevale, Ted, Majumdar, Amit, Sivagnanam, Subhashini, Yoshimoto, Kenneth, Smirnova, Elena Y, Amakhin, Dmitry V, Malkin, Sergey L, Zaitsev, Aleksey V, Chizhov, Anton V, Zaleshina, Margarita, Zaleshin, Alexander, Barranca, Victor J, Zhu, George, Skilling, Quinton M, Maruyama, Daniel, Ognjanovski, Nicolette, Aton, Sara J, Zochowski, Michal, Wu, Jiaxing, Aton, Sara, Rich, Scott, Booth, Victoria, Budak, Maral, Bernal, Salvador, Neymotin, Samuel A, Suter, Benjamin A, Shepherd, Gordon M G, Felton, Melvin A, Yu, Alfred B, Boothe, David L, Oie, Kelvin S, Franaszczuk, Piotr J, Shuvaev, Sergey A, Başerdem, Batuhan, Zador, Anthony, Koulakov, Alexei A, Madrona, Víctor J, Pereda, Ernesto, Mirasso, Claudio R, Canals, Santiago, Masoli, Stefano, Rongala, Udaya B, Spanne, Anton, Jorntell, Henrik, Oddo, Calogero M, Vartanov, Alexander V, Neklyudova, Anastasia K, Kozlovskiy, Stanislav A, Kiselnikov, Andrey A, Marakshina, Julia A, Teleńczuk, Maria, Teleńczuk, Bartosz, Destexhe, Alain, Kuokkanen, Paula T, Kraemer, Anna, McColgan, Thomas, Carr, Catherine E, Kempter, Richard, Newton, Adam J H, Seidenstein, Alexandra H, McDougal, Robert A, Cervera, Alberto, Huguet, Gemma, Seara, Tere, Haimerl, Caroline, Garcia, David, Torcini, Alessandro, Cossart, Rosa, Malvache, Arnaud, Skiker, Kaoutar, Maouene, Mounir, Ragognetti, Gianmarco, Lorusso, Letizia, Viggiano, Andrea, Marcelli, Angelo, Senatore, Rosa, Parziale, Antonio, Stramaglia, S., Pellicoro, M., Angelini, L., Amico, E., Aerts, H., Cortés, J., Laureys, S., Marinazzo, D., Bassez, I., Faes, L., Almgren, Hannes, Razi, Adeel, Steen, Frederik, Krebs, Ruth, Aerts, Hannelore, Kanari, Lida, Dlotko, Pawel, Scolamiero, Martina, Levi, Ran, Shillcock, Julian, Kock, Christiaan P, Hess, Kathryn, Markram, Henry, Ly, Cheng, Marsat, Gary, Gillespie, Tom, Sandström, Malin, Abrams, Mathew, Grethe, Jeffrey S, Martone, Maryann, Gernier, Robin, Solinas, Sergio, Rössert, Christian, Haelterman, Marc, Massar, Serge, Pasquale, Valentina, Pastore, Vito P, Martinoia, Sergio, Massobrio, Paolo, Capone, Cristiano, Colet, Núria, Vives, Maria V, Mattia, Maurizio, Almasi, Ali, Cloherty, Shaun L, Grayden, David B, Wong, Yan T, Ibbotson, Michael R, Meffin, Hamish, Prince, Luke Y, Atanasova, Krasimira, Mellor, Jack R, Mazzoni, Alberto, Rosa, Manuela, Carpaneto, Jacopo, Romito, Luigi M, Priori, Alberto, Micera, Silvestro, Migliore, Rosanna, Lupascu, Carmen A, Franchina, Francesco, Bologna, Luca L, Romani, Armando, Saray, Sára, Geit, Werner, Káli, Szabolcs, Thomson, Alex, Mercer, Audrey, Lange, Sigrun, Falck, Joanne, Muller, Eilif, Schürmann, Felix, Todorov, Dmitrii, Capps, Robert, Barnett, William, Molkov, Yaroslav, Devalle, Federico, Pazó, Diego, Montbrió, Ernest, Mochol, Gabriela, Azab, Habiba, Hayden, Benjamin Y, Bote, Rubén, Balasubramani, Pragathi P, Chakravarthy, Srinivasa V, Muddapu, Vignayanandam R, Gheorghiu, Medorian D, Mimica, Bartul, Withlock, Jonathan, Mureșan, Raul C, Zick, Jennifer L, Schultz, Kelsey, Blackman, Rachael K, Chafee, Matthew V, Netoff, Theoden I, Roberts, Nicholas, Nagaraj, Vivek, Lamperski, Andrew, Grado, Logan L, Johnson, Matthew D, Darrow, David P, Lonardoni, Davide, Amin, Hayder, Marco, Stefano, Maccione, Alessandro, Berdondini, Luca, Nieus, Thierry, Stimberg, Marcel, Goodman, Dan F M, Nowotny, Thomas, Koren, Veronika, Dragoi, Valentin, Obermayer, Klaus, Castro, Samy, Fernandez, Mariano, Deredy, Wael, Xu, Kesheng, Maidana, Jean P, Orio, Patricio, Chen, Weiliang, Hepburn, Iain, Casalegno, Francesco, Devresse, Adrien, Ovcharenko, Aleksandr, Pereira, Fernando, Delalondre, Fabien, Schutter, Erik, Bratby, Peter, Gallimore, Andrew R, Klingbeil, Guido, Zamora, Criseida, Zang, Yunliang, Crotty, Patrick, Palmerduca, Eric, Antonietti, Alberto, Casellato, Claudia, Erö, Csaba, Angelo, Egidio, Gewaltig, Marc-Oliver, Pedrocchi, Alessandra, Bytschok, Ilja, Dold, Dominik, Schemmel, Johannes, Meier, Karlheinz, Petrovici, Mihai A, Shen, Hui-An, Surace, Simone C, Pfister, Jean-Pascal, Lefebvre, Baptiste, Marre, Olivier, Yger, Pierre, Papoutsi, Athanasia, Park, Jiyoung, Ash, Ryan, Smirnakis, Stelios, Poirazi, Panayiota, Felix, Richard A, Dimitrov, Alexander G, Portfors, Christine, Daun, Silvia, Toth, Tibor I, Szmek, Joanna, Kabbani, Nadine, Blackwel, Kim T, Moezzi, Bahar, Schaworonkow, Natalie, Plogmacher, Lukas, Goldsworthy, Mitchell R, Hordacre, Brenton, McDonnell, Mark D, Iannella, Nicolangelo, Ridding, Michael C, Triesch, Jochen, Maex, Reinoud, Safaryan, Karen, Steuber, Volker, Tang, Rongxiang, Tang, Yi-Yuan, Verveyko, Darya V, Brazhe, Alexey R, Verisokin, Andrey Y, Postnov, Dmitry E, Günay, Cengiz, Panuccio, Gabriella, Giugliano, Michele, Prinz, Astrid A, Varona, Pablo, Rabinovich, Mikhail I, Denham, Jack, Ranner, Thomas, Cohen, Netta, Reva, Maria, Rebola, Nelson, Kirizs, Tekla, Nusser, Zoltan, DiGregorio, David, Mavritsaki, Eirini, Rentzelas, Panos, Ukani, Nikul H, Tomkins, Adam, Yeh, Chung-Heng, Bruning, Wesley, Fenichel, Allison L, Zhou, Yiyin, Huang, Yu-Chi, Florescu, Dorian, Ortiz, Carlos L, Richmond, Paul, Lo, Chung-Chuan, Coca, Daniel, Chiang, Ann-Shyn, Lazar, Aurel A, Creaser, Jennifer L, Lin, Congping, Ashwin, Peter, Brown, Jonathan T, Ridler, Thomas, Levenstein, Daniel, Watson, Brendon O, Buzsáki, György, Rinzel, John, Curtu, Rodica, Nguyen, Anh, Assadzadeh, Sahand, Robinson, Peter A, Leon, Paula, Forlim, Caroline G, Almeida, Lírio O B, Pinto, Reynaldo D, Rodríguez, Francisco B, Lareo, Ángel, Montero, Aaron, Mosqueiro, Thiago, Huerta, Ramon, Rodriguez, Francisco B, Changoluisa, Vinicio, Cordeiro, Vinícius L, Ceballos, César C, Kamiji, Nilton L, Roque, Antonio C, Lytton, William W, Knox, Andrew, Rosenthal, Joshua J C, Popovych, Svitlana, Liu, Liqing, Wang, Bin A, Tóth, Tibor I, Grefkes, Christian, Fink, Gereon R, Rosjat, Nils, Trujillo, Abraham, Espinal, Andres, Figueroa, Marco A, Aceves, Ivan, Gonzalez, Horacio, Zapotocky, Martin, Hoskovcová, Martina, Kopecká, Jana, Ulmanová, Olga, Růžička, Evžen, Gärtner, Matthias, Duvarci, Sevil, Roeper, Jochen, Schneider, Gaby, Albert, Stefan, Schmack, Katharina, Remme, Michiel, Schreiber, Susanne, Migliore, Michele, Antonel, Stefano M, Courcol, Jean-Denis, Çelikok, Sami U, López, Eva M, Şengör, Neslihan S, Elibol, Rahmi, Sengor, Neslihan S, Özdemir, Mustafa Y, Li, Tianyi, Arleo, Angelo, Sheynikhovich, Denis, Nakamura, Akihiro, Shimono, Masanori, Song, Youngjo, Park, Sol, Choi, Ilhwan, Jeong, Jaeseung, Shin, Hee-sup, Sadeh, Sadra, Gleeson, Padraig, Silver, R., Chatzikalymniou, Alexandra P, Skinner, Frances K, Rodriguez, Lazaro M, Sotero, Roberto C, Hertäg, Loreen, Mackwood, Owen, Sprekeler, Henning, Puhlmann, Steffen, Weber, Simon N, Higgins, David, Naumann, Laura B, Iyer, Ramakrisnan, Mihalas, Stefan, Ticcinelli, Valentina, Stankovski, Tomislav, McClintock, Peter V E, Stefanovska, Aneta, Janjić, Predrag, Solev, Dimitar, Seifert, Gerald, Kocarev, Ljupčo, Steinhäuser, Christian, Salmasi, Mehrdad, Glasauer, Stefan, Stemmler, Martin, Zhang, Danke, Zhang, Chi, Stepanyants, Armen, Goncharenko, Julia, Kros, Lieke, Davey, Neil, Zeeuw, Chris, Hoebeek, Freek, Sinha, Ankur, Adams, Roderick, Schmuker, Michael, Psarrou, Maria, Schilstra, Maria, Nielsen, Benjamin, Metzner, Christoph, Schweikard, Achim, Marttunen, Tuomo, Zurowski, Bartosz, Marinazzo, Daniele, Faes, Luca, Stramaglia, Sebastiano, Jordan, Henry O C, Stringer, Simon M, Dendek, Elżbieta, Suffczyński, Piotr, Tam, Nicoladie, Zouridakis, George, Pollonini, Luca, Asl, Mojtaba M, Valizadeh, Alireza, Tass, Peter A, Nold, Andreas, Fan, Wei, Konrad, Sara, Endle, Heiko, Vogt, Johannes, Tchumatchenko, Tatjana, Herpich, Juliane, Tetzlaff, Christian, Luboeinski, Jannik, Nachstedt, Timo, Ciba, Manuel, Bahmer, Andreas, Thielemann, Christiane, Kuebler, Eric S, Tauskela, Joseph S, Thivierge, Jean-Philippe, Bakker, Rembrandt, Amado, María, Evangelio, Marian, Clascá, Francisco, Tiesinga, Paul, Buckley, Christopher L, Toyoizumi, Taro, Dubreuil, Alexis M, Monasson, Rémi, Treves, Alessandro, Spalla, Davide, Rosay, Sophie, Kleberg, Florence I, Wong, Willy, Floriano, Bruno, Matsuo, Toshihiko, Uchida, Tetsuya, Dibenedetto, Domenica, Uludağ, Kâmil, Goodarzinick, Abdorreza, Schmidt, Maximilian, Hilgetag, Claus C, Diesmann, Markus, Albada, Sacha J, Fauth, Michael, Rossum, Mark, Sánchez, Manuel, Amaducci, Rodrigo, Muñiz, Carlos, Elices, Irene, Arroyo, David, Levi, Rafael, Cohen, Ben, Chow, Carson, Vattikuti, Shashaank, Bertolotti, Elena, Burioni, Raffaella, Volo, Matteo, Vezzani, Alessandro, Menzat, Bayar, Vogels, Tim P, Wagatsuma, Nobuhiko, Saha, Susmita, Kapoor, Reena, Kerr, Robert, Wagner, John, Molino, Luis C G, Yang, Guangyu R, Mejias, Jorge F, Wang, Xiao-Jing, Song, Hanbing, Goodliffe, Joseph, Luebke, Jennifer, Weaver, Christina M, Thomas, John, Sinha, Nishant, Shaju, Nikhita, Maszczyk, Tomasz, Jin, Jing, Cash, Sydney S, Dauwels, Justin, Westover, M., Karimian, Maryam, Moerel, Michelle, Weerd, Peter, Burwick, Thomas, Westra, Ronald L, Abeysuriya, Romesh, Hadida, Jonathan, Sotiropoulos, Stamatios, Jbabdi, Saad, Woolrich, Mark, Bensmail, Chama, Wrobel, Borys, Zhou, Xiaolong, Ji, Zilong, Liu, Xiao, Xia, Yan, Wu, Si, Wang, Xiao, Zhang, Mingsha, Ofer, Netanel, Shefi, Orit, Yaari, Gur, Carnevale, Ted, Majumdar, Amit, Sivagnanam, Subhashini, Yoshimoto, Kenneth, Smirnova, Elena Y, Amakhin, Dmitry V, Malkin, Sergey L, Zaitsev, Aleksey V, Chizhov, Anton V, Zaleshina, Margarita, Zaleshin, Alexander, Barranca, Victor J, Zhu, George, Skilling, Quinton M, Maruyama, Daniel, Ognjanovski, Nicolette, Aton, Sara J, Zochowski, Michal, Wu, Jiaxing, Aton, Sara, Rich, Scott, Booth, Victoria, Budak, Maral, Bernal, Salvador, Neymotin, Samuel A, Suter, Benjamin A, Shepherd, Gordon M G, Felton, Melvin A, Yu, Alfred B, Boothe, David L, Oie, Kelvin S, Franaszczuk, Piotr J, Shuvaev, Sergey A, Başerdem, Batuhan, Zador, Anthony, Koulakov, Alexei A, Madrona, Víctor J, Pereda, Ernesto, Mirasso, Claudio R, Canals, Santiago, Masoli, Stefano, Rongala, Udaya B, Spanne, Anton, Jorntell, Henrik, Oddo, Calogero M, Vartanov, Alexander V, Neklyudova, Anastasia K, Kozlovskiy, Stanislav A, Kiselnikov, Andrey A, Marakshina, Julia A, Teleńczuk, Maria, Teleńczuk, Bartosz, Destexhe, Alain, Kuokkanen, Paula T, Kraemer, Anna, McColgan, Thomas, Carr, Catherine E, and Kempter, Richard

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2017
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38. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Author

Newton, Adam J. H., primary, Seidenstein, Alexandra H., additional, McDougal, Robert A., additional, Pérez-Cervera, Alberto, additional, Huguet, Gemma, additional, M-Seara, Tere, additional, Haimerl, Caroline, additional, Angulo-Garcia, David, additional, Torcini, Alessandro, additional, Cossart, Rosa, additional, Malvache, Arnaud, additional, Skiker, Kaoutar, additional, Maouene, Mounir, additional, Ragognetti, Gianmarco, additional, Lorusso, Letizia, additional, Viggiano, Andrea, additional, Marcelli, Angelo, additional, Senatore, Rosa, additional, Parziale, Antonio, additional, Stramaglia, S., additional, Pellicoro, M., additional, Angelini, L., additional, Amico, E., additional, Aerts, H., additional, Cortés, J., additional, Laureys, S., additional, Marinazzo, D., additional, Bassez, I., additional, Faes, L., additional, Almgren, Hannes, additional, Razi, Adeel, additional, Van de Steen, Frederik, additional, Krebs, Ruth, additional, Aerts, Hannelore, additional, Kanari, Lida, additional, Dlotko, Pawel, additional, Scolamiero, Martina, additional, Levi, Ran, additional, Shillcock, Julian, additional, de Kock, Christiaan P.J., additional, Hess, Kathryn, additional, Markram, Henry, additional, Ly, Cheng, additional, Marsat, Gary, additional, Gillespie, Tom, additional, Sandström, Malin, additional, Abrams, Mathew, additional, Grethe, Jeffrey S., additional, Martone, Maryann, additional, De Gernier, Robin, additional, Solinas, Sergio, additional, Rössert, Christian, additional, Haelterman, Marc, additional, Massar, Serge, additional, Pasquale, Valentina, additional, Pastore, Vito Paolo, additional, Martinoia, Sergio, additional, Massobrio, Paolo, additional, Capone, Cristiano, additional, Tort-Colet, Núria, additional, Sanchez-Vives, Maria V., additional, Mattia, Maurizio, additional, Almasi, Ali, additional, Cloherty, Shaun L., additional, Grayden, David B., additional, Wong, Yan T., additional, Ibbotson, Michael R., additional, Meffin, Hamish, additional, Prince, Luke Y., additional, Tsaneva-Atanasova, Krasimira, additional, Mellor, Jack R., additional, Mazzoni, Alberto, additional, Rosa, Manuela, additional, Carpaneto, Jacopo, additional, Romito, Luigi M., additional, Priori, Alberto, additional, Micera, Silvestro, additional, Migliore, Rosanna, additional, Lupascu, Carmen Alina, additional, Franchina, Francesco, additional, Bologna, Luca Leonardo, additional, Romani, Armando, additional, Saray, Sára, additional, Van Geit, Werner, additional, Káli, Szabolcs, additional, Thomson, Alex, additional, Mercer, Audrey, additional, Lange, Sigrun, additional, Falck, Joanne, additional, Muller, Eilif, additional, Schürmann, Felix, additional, Todorov, Dmitrii, additional, Capps, Robert, additional, Barnett, William, additional, Molkov, Yaroslav, additional, Devalle, Federico, additional, Pazó, Diego, additional, Montbrió, Ernest, additional, Mochol, Gabriela, additional, Azab, Habiba, additional, Hayden, Benjamin Y., additional, Moreno-Bote, Rubén, additional, Balasubramani, Pragathi Priyadharsini, additional, Chakravarthy, Srinivasa V., additional, Muddapu, Vignayanandam R., additional, Gheorghiu, Medorian D., additional, Mimica, Bartul, additional, Withlock, Jonathan, additional, Mureșan, Raul C., additional, Zick, Jennifer L., additional, Schultz, Kelsey, additional, Blackman, Rachael K., additional, Chafee, Matthew V., additional, Netoff, Theoden I., additional, Roberts, Nicholas, additional, Nagaraj, Vivek, additional, Lamperski, Andrew, additional, Grado, Logan L., additional, Johnson, Matthew D., additional, Darrow, David P., additional, Lonardoni, Davide, additional, Amin, Hayder, additional, Di Marco, Stefano, additional, Maccione, Alessandro, additional, Berdondini, Luca, additional, Nieus, Thierry, additional, Stimberg, Marcel, additional, Goodman, Dan F. M., additional, Nowotny, Thomas, additional, Koren, Veronika, additional, Dragoi, Valentin, additional, Obermayer, Klaus, additional, Castro, Samy, additional, Fernandez, Mariano, additional, El-Deredy, Wael, additional, Xu, Kesheng, additional, Maidana, Jean Paul, additional, Orio, Patricio, additional, Chen, Weiliang, additional, Hepburn, Iain, additional, Casalegno, Francesco, additional, Devresse, Adrien, additional, Ovcharenko, Aleksandr, additional, Pereira, Fernando, additional, Delalondre, Fabien, additional, De Schutter, Erik, additional, Bratby, Peter, additional, Gallimore, Andrew R., additional, Klingbeil, Guido, additional, Zamora, Criseida, additional, Zang, Yunliang, additional, Crotty, Patrick, additional, Palmerduca, Eric, additional, Antonietti, Alberto, additional, Casellato, Claudia, additional, Erö, Csaba, additional, D’Angelo, Egidio, additional, Gewaltig, Marc-Oliver, additional, Pedrocchi, Alessandra, additional, Bytschok, Ilja, additional, Dold, Dominik, additional, Schemmel, Johannes, additional, Meier, Karlheinz, additional, Petrovici, Mihai A., additional, Shen, Hui-An, additional, Surace, Simone Carlo, additional, Pfister, Jean-Pascal, additional, Lefebvre, Baptiste, additional, Marre, Olivier, additional, Yger, Pierre, additional, Papoutsi, Athanasia, additional, Park, Jiyoung, additional, Ash, Ryan, additional, Smirnakis, Stelios, additional, Poirazi, Panayiota, additional, Felix, Richard A., additional, Dimitrov, Alexander G., additional, Portfors, Christine, additional, Daun, Silvia, additional, Toth, Tibor I., additional, Jędrzejewska-Szmek, Joanna, additional, Kabbani, Nadine, additional, Blackwel, Kim T., additional, Moezzi, Bahar, additional, Schaworonkow, Natalie, additional, Plogmacher, Lukas, additional, Goldsworthy, Mitchell R., additional, Hordacre, Brenton, additional, McDonnell, Mark D., additional, Iannella, Nicolangelo, additional, Ridding, Michael C., additional, Triesch, Jochen, additional, Maex, Reinoud, additional, Safaryan, Karen, additional, Steuber, Volker, additional, Tang, Rongxiang, additional, Tang, Yi-Yuan, additional, Verveyko, Darya V., additional, Brazhe, Alexey R., additional, Verisokin, Andrey Yu, additional, Postnov, Dmitry E., additional, Günay, Cengiz, additional, Panuccio, Gabriella, additional, Giugliano, Michele, additional, Prinz, Astrid A., additional, Varona, Pablo, additional, Rabinovich, Mikhail I., additional, Denham, Jack, additional, Ranner, Thomas, additional, Cohen, Netta, additional, Reva, Maria, additional, Rebola, Nelson, additional, Kirizs, Tekla, additional, Nusser, Zoltan, additional, DiGregorio, David, additional, Mavritsaki, Eirini, additional, Rentzelas, Panos, additional, Ukani, Nikul H., additional, Tomkins, Adam, additional, Yeh, Chung-Heng, additional, Bruning, Wesley, additional, Fenichel, Allison L., additional, Zhou, Yiyin, additional, Huang, Yu-Chi, additional, Florescu, Dorian, additional, Ortiz, Carlos Luna, additional, Richmond, Paul, additional, Lo, Chung-Chuan, additional, Coca, Daniel, additional, Chiang, Ann-Shyn, additional, Lazar, Aurel A., additional, Creaser, Jennifer L., additional, Lin, Congping, additional, Ashwin, Peter, additional, Brown, Jonathan T., additional, Ridler, Thomas, additional, Levenstein, Daniel, additional, Watson, Brendon O., additional, Buzsáki, György, additional, Rinzel, John, additional, Curtu, Rodica, additional, Nguyen, Anh, additional, Assadzadeh, Sahand, additional, Robinson, Peter A., additional, Sanz-Leon, Paula, additional, Forlim, Caroline G., additional, de Almeida, Lírio O. B., additional, Pinto, Reynaldo D., additional, Rodríguez, Francisco B., additional, Lareo, Ángel, additional, Forlim, Caroline Garcia, additional, Montero, Aaron, additional, Mosqueiro, Thiago, additional, Huerta, Ramon, additional, Rodriguez, Francisco B., additional, Changoluisa, Vinicio, additional, Cordeiro, Vinícius L., additional, Ceballos, César C., additional, Kamiji, Nilton L., additional, Roque, Antonio C., additional, Lytton, William W., additional, Knox, Andrew, additional, Rosenthal, Joshua J. C., additional, Popovych, Svitlana, additional, Liu, Liqing, additional, Wang, Bin A., additional, Tóth, Tibor I., additional, Grefkes, Christian, additional, Fink, Gereon R., additional, Rosjat, Nils, additional, Perez-Trujillo, Abraham, additional, Espinal, Andres, additional, Sotelo-Figueroa, Marco A., additional, Cruz-Aceves, Ivan, additional, Rostro-Gonzalez, Horacio, additional, Zapotocky, Martin, additional, Hoskovcová, Martina, additional, Kopecká, Jana, additional, Ulmanová, Olga, additional, Růžička, Evžen, additional, Gärtner, Matthias, additional, Duvarci, Sevil, additional, Roeper, Jochen, additional, Schneider, Gaby, additional, Albert, Stefan, additional, Schmack, Katharina, additional, Remme, Michiel, additional, Schreiber, Susanne, additional, Migliore, Michele, additional, Lupascu, Carmen A., additional, Bologna, Luca L., additional, Antonel, Stefano M., additional, Courcol, Jean-Denis, additional, Çelikok, Sami Utku, additional, Navarro-López, Eva M., additional, Şengör, Neslihan Serap, additional, Elibol, Rahmi, additional, Sengor, Neslihan Serap, additional, Özdemir, Mustafa Yasir, additional, Li, Tianyi, additional, Arleo, Angelo, additional, Sheynikhovich, Denis, additional, Nakamura, Akihiro, additional, Shimono, Masanori, additional, Song, Youngjo, additional, Park, Sol, additional, Choi, Ilhwan, additional, Jeong, Jaeseung, additional, Shin, Hee-sup, additional, Sadeh, Sadra, additional, Gleeson, Padraig, additional, Angus Silver, R., additional, Chatzikalymniou, Alexandra Pierri, additional, Skinner, Frances K., additional, Sanchez-Rodriguez, Lazaro M., additional, Sotero, Roberto C., additional, Hertäg, Loreen, additional, Mackwood, Owen, additional, Sprekeler, Henning, additional, Puhlmann, Steffen, additional, Weber, Simon N., additional, Higgins, David, additional, Naumann, Laura B., additional, Iyer, Ramakrisnan, additional, Mihalas, Stefan, additional, Ticcinelli, Valentina, additional, Stankovski, Tomislav, additional, McClintock, Peter V. E., additional, Stefanovska, Aneta, additional, Janjić, Predrag, additional, Solev, Dimitar, additional, Seifert, Gerald, additional, Kocarev, Ljupčo, additional, Steinhäuser, Christian, additional, Salmasi, Mehrdad, additional, Glasauer, Stefan, additional, Stemmler, Martin, additional, Zhang, Danke, additional, Zhang, Chi, additional, Stepanyants, Armen, additional, Goncharenko, Julia, additional, Kros, Lieke, additional, Davey, Neil, additional, de Zeeuw, Chris, additional, Hoebeek, Freek, additional, Sinha, Ankur, additional, Adams, Roderick, additional, Schmuker, Michael, additional, Psarrou, Maria, additional, Schilstra, Maria, additional, Torben-Nielsen, Benjamin, additional, Metzner, Christoph, additional, Schweikard, Achim, additional, Mäki-Marttunen, Tuomo, additional, Zurowski, Bartosz, additional, Marinazzo, Daniele, additional, Faes, Luca, additional, Stramaglia, Sebastiano, additional, Jordan, Henry O. 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Published
2017
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45. The Identification of Dynamic Gene-Protein Networks.

Author

Istrail, Sorin, Pevzner, Pavel, Waterman, Michael S., Tuyls, Karl, Westra, Ronald, Saeys, Yvan, Nowé, Ann, Westra, Ronald L., Hollanders, Goele, Bex, Geert Jan, and Gyssens, Marc

Abstract

In this study we will focus on piecewise linear state space models for gene-protein interaction networks. We will follow the dynamical systems approach with special interest for partitioned state spaces. From the observation that the dynamics in natural systems tends to punctuated equilibria, we will focus on piecewise linear models and sparse and hierarchic interactions, as, for instance, described by Glass, Kauffman, and de Jong. Next, the paper is concerned with the identification (also known as reverse engineering and reconstruction) of dynamic genetic networks from microarray data. We will describe exact and robust methods for computing the interaction matrix in the special case of piecewise linear models with sparse and hierarchic interactions from partial observations. Finally, we will analyze and evaluate this approach with regard to its performance and robustness towards intrinsic and extrinsic noise. [ABSTRACT FROM AUTHOR]

Published
2007
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46. Learning Sparse Networks From Poor Data

Author

HOLLANDERS, Goele, BEX, Geert Jan, GYSSENS, Marc, WESTRA, Ronald, and TUYLS, Karl

Subjects
machine learning, sparse systems, network reconstruction
Abstract

This paper is concerned with the learning process of a sparse interaction network, for example, a gene-protein interaction network. The advantage of the process we purpose is that there will always be a student S that fits the teacher T very well with a relatively small data set and a high number of unknown components, i.e., when the number of measurements M is significantly smaller than the system size N. To measure the efficiency of this learning process, we use the generalization error, epsilon_gen, which represents the probability that the student is a good fit to the teacher. From our experiments it follows that the quality of the fit depends on several factors: First, the ratio α = M/N of the number of measurements to the system size has a strong impact. Surprisingly, we find that a sudden identification transition occurs for value α ≈ αgen which corresponds to epsilon_gen = 1/2. From this sample size onwards the student will be a good fit to the teacher. Interestingly, the generalization threshold αgen, will always be significantly smaller than 1. Second, the quality of the fit depends on the sparsity of the network. If the number of non-zero components increases, as sparsity disappears, the efficiency of the process will gradually increase. Finally there is an impact of the noise level. The learning process is robust to noise upto a certain threshold. We see that, at this level, the impact on the noise suddenly and dramatically increases as a consequence of which the student will no longer be a good fit to the teacher.

Published
2007

47. The pattern memory of gene-protein networks

Author

Westra, Ronald L., Hollanders, Goele, Bex, Geert Jan, Gyssens, Marc, and Karl Tuyls

Subjects
gene-protein networks, pattern memory, linear state space models, phase transitions, information entropy
Abstract

In this paper we study the potential of gene-protein interaction networks to store input-output patterns. The central question in this study concerns the memory capacity of a network of a given number of genes and proteins, which interact according to a linear state space model with external inputs. Here it is assumed that to a certain combination of inputs there exists an optimal state of the system, i.e., values of the gene expressions and protein levels, that has been attained externally, e.g., through evolutionary learning. Given such a set of learned optimal input-output patterns, the design question here is to find a sparse and hierarchical network structure for the gene-protein interactions and the gene-input couplings. This problem is formulated as an optimization problem in a linear programming setting. Numerical analysis shows that there are clear scale-invariant continuous second-order phase transitions for the network sparsity as the number of patterns increases. These phase transitions divide the system in three regions with different memory characteristics. It is possible to formulate simple scaling rules for the behavior of the network sparsity. Finally, numerical experiments show that these patterns are stable within a certain finite range around the patterns.

Published
2007

48. The Identification of Dynamic Gene-Protein Networks

Author

WESTRA, Ronald, HOLLANDERS, Goele, BEX, Geert Jan, GYSSENS, Marc, and TUYLS, Karl

Subjects
piecewise linear model, robust identification, hierarchical networks, microarrays
Abstract

In this study we will focus on piecewise linear state space models for gene-protein interaction networks. We will follow the dynamical systems approach with special interest for partitioned state spaces. From the observation that the dynamics in natural systems tends to punctuated equilibria, we will focus on piecewise linear models and sparse and hierarchic interactions, as, for instance, described by Glass, Kauffman, and de Jong. Next, the paper is concerned with the identification (also known as reverse engineering and reconstruction) of dynamic genetic networks from microarray data. We will describe exact and robust methods for computing the interaction matrix in the special case of piecewise linear models with sparse and hierarchic interactions from partial observations. Finally, we will analyze and evaluate this approach with regard to its performance and robustness towards intrinsic and extrinsic noise.

Published
2007

49. Reconstruction of flexible gene-protein interaction networks using piecewise linear modeling and robust regression

Author

WESTRA, Ronald, Peeters, R.L.M., HOLLANDERS, Goele, and TUYLS, Karl

Subjects
piecewise linear, robust identi_cation, hierarchical networks, gene expression data, gene regulatory networks
Abstract

In this study we will focus on piece-wise linear state space models for gene-protein interaction networks. We will follow the dynamical systems approach with special interest for partitioned state spaces. From the observation that the dynamics in natural systems tends to punctuated equilibria, we will focus on piecewise linear models and sparse and hierarchic interactions, as for instance described by Glass, Kauffman, and de Jong. Next, the paper is concerned with the identi_cation (a.k.a. reverse engineering and reconstruction) of dynamic genetic networks from microarray data. We will describe exact and robust methods for computing the interaction matrix in the special case of piecewise linear models with sparse and hierarchic interactions from partial observations. Finally, we will analyze and evaluate this approach with regard to its performance and robustness towards intrinsic and extrinsic noise.

Published
2006

50. Network topology of NaV1.7 mutations in sodium channel-related painful disorders.

Author

Kapetis, Dimos, Sassone, Jenny, Yang Yang, Galbardi, Barbara, Xenakis, Markos N., Westra, Ronald L., Szklarczyk, Radek, Lindsey, Patrick, Faber, Catharina G., Gerrits, Monique, Merkies, Ingemar S. J., Dib-Hajj, Sulayman D., Mantegazza, Massimo, Waxman, Stephen G., and Lauria, Giuseppe

Subjects
SODIUM channels, PAIN, ERYTHROMELALGIA, STRUCTURAL models, GENETIC polymorphisms
Abstract

Background: Gain-of-function mutations in SCN9A gene that encodes the voltage-gated sodium channel NaV1.7 have been associated with a wide spEctrum of painful syndromes in humans including inherited erythromelalgia, paroxysmal extreme pain disorder and small fibre neuropathy. These mutations change the biophysical properties of NaV1.7 channels leading to hyperexcitability of dorsal root ganglion nociceptors and pain symptoms. There is a need for better understanding of how gain-of-function mutations alter the atomic structure of Nav1.7. Results: We used homology modeling to build an atomic model of NaV1.7 and a network-based theoretical approach, which can predict interatomic interactions and connEctivity arrangements, to investigate how pain-related NaV1.7 mutations may alter specific interatomic bonds and cause connEctivity rearrangement, compared to benign variants and polymorphisms. For each amino acid substitution, we calculated the topological parameters betweenness centrality (Bct), degree (D), clustering coefficient (CCct), closeness (Cct), and eccentricity (Ect), and calculated their variation (Δvalue=mutant value-WT value). Pathogenic NaV1.7 mutations showed significantly higher variation of ∣ΔBct∣ compared to benign variants and polymorphisms. Using the cut-off value ±0.26 calculated by receiver operating curve analysis, we found that ΔBct corrEctly differentiated pathogenic NaV1.7 mutations from variants not causing biophysical abnormalities (nABN) and homologous SNPs (hSNPs) with 76% sensitivity and 83% specificity. Conclusions: Our in-silico analyses predict that pain-related pathogenic NaV1.7 mutations may affEct the network topological properties of the protein and suggest ∣ΔBct∣ value as a potential in-silico marker. [ABSTRACT FROM AUTHOR]

Published
2017
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