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2. Mol-PECO: a deep learning model to predict human olfactory perception from molecular structures

Author

Zhang, Mengji, Hiki, Yusuke, Funahashi, Akira, and Kobayashi, Tetsuya J.

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Quantitative Biology - Biomolecules, Quantitative Biology - Neurons and Cognition
Abstract

While visual and auditory information conveyed by wavelength of light and frequency of sound have been decoded, predicting olfactory information encoded by the combination of odorants remains challenging due to the unknown and potentially discontinuous perceptual space of smells and odorants. Herein, we develop a deep learning model called Mol-PECO (Molecular Representation by Positional Encoding of Coulomb Matrix) to predict olfactory perception from molecular structures. Mol-PECO updates the learned atom embedding by directional graph convolutional networks (GCN), which model the Laplacian eigenfunctions as positional encoding, and Coulomb matrix, which encodes atomic coordinates and charges. With a comprehensive dataset of 8,503 molecules, Mol-PECO directly achieves an area-under-the-receiver-operating-characteristic (AUROC) of 0.813 in 118 odor descriptors, superior to the machine learning of molecular fingerprints (AUROC of 0.761) and GCN of adjacency matrix (AUROC of 0.678). The learned embeddings by Mol-PECO also capture a meaningful odor space with global clustering of descriptors and local retrieval of similar odorants. Our work may promote the understanding and decoding of the olfactory sense and mechanisms., Comment: 17 pages, 8 figures

Published
2023

3. BioSimulators: a central registry of simulation engines and services for recommending specific tools

Author

Shaikh, Bilal, Smith, Lucian P., Vasilescu, Dan, Marupilla, Gnaneswara, Wilson, Michael, Agmon, Eran, Agnew, Henry, Andrews, Steven S., Anwar, Azraf, Beber, Moritz E., Bergmann, Frank T., Brooks, David, Brusch, Lutz, Calzone, Laurence, Choi, Kiri, Cooper, Joshua, Detloff, John, Drawert, Brian, Dumontier, Michel, Ermentrout, G. Bard, Faeder, James R., Freiburger, Andrew P., Fröhlich, Fabian, Funahashi, Akira, Garny, Alan, Gennari, John H., Gleeson, Padraig, Goelzer, Anne, Haiman, Zachary, Hellerstein, Joseph L., Hoops, Stefan, Ison, Jon C., Jahn, Diego, Jakubowski, Henry V., Jordan, Ryann, Kalaš, Matúš, König, Matthias, Liebermeister, Wolfram, Mandal, Synchon, McDougal, Robert, Medley, J. Kyle, Mendes, Pedro, Müller, Robert, Myers, Chris J., Naldi, Aurelien, Nguyen, Tung V. N., Nickerson, David P., Olivier, Brett G., Patoliya, Drashti, Paulevé, Loïc, Petzold, Linda R., Priya, Ankita, Rampadarath, Anand K., Rohwer, Johann M., Saglam, Ali S., Singh, Dilawar, Sinha, Ankur, Snoep, Jacky, Sorby, Hugh, Spangler, Ryan, Starruß, Jörn, Thomas, Payton J., van Niekerk, David, Weindl, Daniel, Zhang, Fengkai, Zhukova, Anna, Goldberg, Arthur P., Blinov, Michael L., Sauro, Herbert M., Moraru, Ion I., and Karr, Jonathan R.

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computational Engineering, Finance, and Science, Quantitative Biology - Molecular Networks
Abstract

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line, and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML, and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations., Comment: 6 pages, 2 figures

Published
2022

4. Symbolic integration by integrating learning models with different strengths and weaknesses

Author

Kubota, Hazumi, Tokuoka, Yuta, Yamada, Takahiro G., and Funahashi, Akira

Subjects
Computer Science - Machine Learning, Computer Science - Symbolic Computation
Abstract

Integration is indispensable, not only in mathematics, but also in a wide range of other fields. A deep learning method has recently been developed and shown to be capable of integrating mathematical functions that could not previously be integrated on a computer. However, that method treats integration as equivalent to natural language translation and does not reflect mathematical information. In this study, we adjusted the learning model to take mathematical information into account and developed a wide range of learning models that learn the order of numerical operations more robustly. In this way, we achieved a 98.80% correct answer rate with symbolic integration, a higher rate than that of any existing method. We judged the correctness of the integration based on whether the derivative of the primitive function was consistent with the integrand. By building an integrated model based on this strategy, we achieved a 99.79% rate of correct answers with symbolic integration.

Published
2021
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6. SBML Level 3: an extensible format for the exchange and reuse of biological models.

Author

Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, and SBML Level 3 Community members

Subjects
SBML Level 3 Community members, Animals, Humans, Logistic Models, Systems Biology, Models, Biological, Software, computational modeling, file format, interoperability, reproducibility, systems biology, Bioengineering, Networking and Information Technology R&D, Bioinformatics, Biochemistry and Cell Biology, Other Biological Sciences
Abstract

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Published
2020

8. SBML level 3 package: spatial processes, version 1, release 1

Author

Schaff James C., Lakshminarayana Anuradha, Murphy Robert F., Bergmann Frank T., Funahashi Akira, Sullivan Devin P., and Smith Lucian P.

Subjects
Biotechnology, TP248.13-248.65
Abstract

While many biological processes can be modeled by abstracting away the space in which those processes occur, some modeling (particularly at the cellular level) requires space itself to be modeled, with processes happening not in well-mixed compartments, but spatially-defined compartments. The SBML Level 3 Core specification does not include an explicit mechanism to encode geometries and spatial processes in a model, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactic constructs. The SBML Spatial Processes package for SBML Level 3 adds the necessary features to allow models to encode geometries and other spatial information about the elements and processes it describes.

Published
2023
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12. The systems biology simulation core algorithm

Author

Keller, Roland, Dörr, Alexander, Tabira, Akito, Funahashi, Akira, Ziller, Michael J, Adams, Richard, Rodriguez, Nicolas, Novère, Nicolas, Hiroi, Noriko, Planatscher, Hannes, Zell, Andreas, and Dräger, Andreas

Abstract

Abstract Background With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases. Results This article describes an efficient algorithm to solve SBML models that are interpreted in terms of ordinary differential equations. We begin our consideration with a formal representation of the mathematical form of the models and explain all parts of the algorithm in detail, including several preprocessing steps. We provide a flexible reference implementation as part of the Systems Biology Simulation Core Library, a community-driven project providing a large collection of numerical solvers and a sophisticated interface hierarchy for the definition of custom differential equation systems. To demonstrate the capabilities of the new algorithm, it has been tested with the entire SBML Test Suite and all models of BioModels Database. Conclusions The formal description of the mathematics behind the SBML format facilitates the implementation of the algorithm within specifically tailored programs. The reference implementation can be used as a simulation backend for Java™-based programs. Source code, binaries, and documentation can be freely obtained under the terms of the LGPL version 3 from http://simulation-core.sourceforge.net. Feature requests, bug reports, contributions, or any further discussion can be directed to the mailing list simulation-core-development@lists.sourceforge.net.

Published
2013

13. Author Correction: COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms

Author

Ostaszewski, Marek, Mazein, Alexander, Gillespie, Marc E., Kuperstein, Inna, Niarakis, Anna, Hermjakob, Henning, Pico, Alexander R., Willighagen, Egon L., Evelo, Chris T., Hasenauer, Jan, Schreiber, Falk, Dräger, Andreas, Demir, Emek, Wolkenhauer, Olaf, Furlong, Laura I., Barillot, Emmanuel, Dopazo, Joaquin, Orta-Resendiz, Aurelio, Messina, Francesco, Valencia, Alfonso, Funahashi, Akira, Kitano, Hiroaki, Auffray, Charles, Balling, Rudi, and Schneider, Reinhard

Published
2020
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14. COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms

Author

Ostaszewski, Marek, Mazein, Alexander, Gillespie, Marc E., Kuperstein, Inna, Niarakis, Anna, Hermjakob, Henning, Pico, Alexander R., Willighagen, Egon L., Evelo, Chris T., Hasenauer, Jan, Schreiber, Falk, Dräger, Andreas, Demir, Emek, Wolkenhauer, Olaf, Furlong, Laura I., Barillot, Emmanuel, Dopazo, Joaquin, Orta-Resendiz, Aurelio, Messina, Francesco, Valencia, Alfonso, Funahashi, Akira, Kitano, Hiroaki, Auffray, Charles, Balling, Rudi, and Schneider, Reinhard

Published
2020
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15. The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows

Author

Katayama, Toshiaki, Arakawa, Kazuharu, Nakao, Mitsuteru, Ono, Keiichiro, Aoki-Kinoshita, Kiyoko F, Yamamoto, Yasunori, Yamaguchi, Atsuko, Kawashima, Shuichi, Chun, Hong-Woo, Aerts, Jan, Aranda, Bruno, Barboza, Lord, Bonnal, Raoul JP, Bruskiewich, Richard, Bryne, Jan C, Fernández, José M, Funahashi, Akira, Gordon, Paul MK, Goto, Naohisa, Groscurth, Andreas, Gutteridge, Alex, Holland, Richard, Kano, Yoshinobu, Kawas, Edward A, Kerhornou, Arnaud, Kibukawa, Eri, Kinjo, Akira R, Kuhn, Michael, Lapp, Hilmar, Lehvaslaiho, Heikki, Nakamura, Hiroyuki, Nakamura, Yasukazu, Nishizawa, Tatsuya, Nobata, Chikashi, Noguchi, Tamotsu, Oinn, Thomas M, Okamoto, Shinobu, Owen, Stuart, Pafilis, Evangelos, Pocock, Matthew, Prins, Pjotr, Ranzinger, René, Reisinger, Florian, Salwinski, Lukasz, Schreiber, Mark, Senger, Martin, Shigemoto, Yasumasa, Standley, Daron M, Sugawara, Hideaki, Tashiro, Toshiyuki, Trelles, Oswaldo, Vos, Rutger A, Wilkinson, Mark D, York, William, Zmasek, Christian M, Asai, Kiyoshi, and Takagi, Toshihisa

Abstract

Abstract Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies.

Published
2010

18. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

Author

Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Yusuke Hiki, Hiroi, Noriko F., Hu, Finterly, Nhung Pham, Ehrhart, Friederike, and Willighagen, Egon L.

Subjects
COVID-19, SYSTEMS biology, COMPUTATIONAL biology, DRUG repositioning, DISEASE mapping
Abstract

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Author

Sanofi, Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), German Research Foundation, Ministero della Salute, European Commission, Generalitat de Catalunya, National Institutes of Health (US), Klaus Tschira Foundation, National Library of Medicine (US), Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, María, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Lal Puniya, Bhanwar, Naldi, Aurelien, Helikar, Tomas, Singh, Vidisha, Fariñas Fernández, Marco, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce de León, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina BalaurIrina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert W., Phair, Robert, Perfetto, Livia, Matthews, Lisa, Balaya Rex, Devasahayam Arokia, Orlic-Milacic, Marija, Monraz Gómez, Luis Cristóbal, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, COVID- Disease Map Community the COVID-19 Disease Map Community, Sanofi, Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), German Research Foundation, Ministero della Salute, European Commission, Generalitat de Catalunya, National Institutes of Health (US), Klaus Tschira Foundation, National Library of Medicine (US), Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc E., Funahashi, Akira, Acencio, Marcio Luis, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro G., Hiki, Yusuke, Hiroi, Noriko F., Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon L., Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Peña-Chilet, María, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara Sadat, Lal Puniya, Bhanwar, Naldi, Aurelien, Helikar, Tomas, Singh, Vidisha, Fariñas Fernández, Marco, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noël, Vincent, Ponce de León, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Luna, Augustin, Piñero, Janet, Furlong, Laura I., Balaur, Irina BalaurIrina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert W., Phair, Robert, Perfetto, Livia, Matthews, Lisa, Balaya Rex, Devasahayam Arokia, Orlic-Milacic, Marija, Monraz Gómez, Luis Cristóbal, De Meulder, Bertrand, Ravel, Jean Marie, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques S., Evelo, Chris T., D’Eustachio, Peter, Schreiber, Falk, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, and COVID- Disease Map Community the COVID-19 Disease Map Community

Abstract

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing., Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors., Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19., Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Published
2023

21. Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning

Author

Komuro, Jin, primary, Tokuoka, Yuta, additional, Seki, Tomohisa, additional, Kusumoto, Dai, additional, Hashimoto, Hisayuki, additional, Katsuki, Toshiomi, additional, Nakamura, Takahiro, additional, Akiba, Yohei, additional, Kuoka, Thukaa, additional, Kimura, Mai, additional, Yamada, Takahiro, additional, Fukuda, Keiichi, additional, Funahashi, Akira, additional, and Yuasa, Shinsuke, additional

Published
2022
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22. A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

Author

Niarakis, Anna, Ostaszewski, Marek, Mazein, Alexander, Kuperstein, Inna, Kutmon, Martina, Gillespie, Marc, Funahashi, Akira, Acencio, Marcio, Hemedan, Ahmed, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Burtscher, Felicia, Yamada, Takahiro, Hiki, Yusuke, Hiroi, Noriko, Hu, Finterly, Pham, Nhung, Ehrhart, Friederike, Willighagen, Egon, Valdeolivas, Alberto, Dugourd, Aurelien, Messina, Francesco, Esteban-Medina, Marina, Pena-Chilet, Maria, Rian, Kinza, Soliman, Sylvain, Aghamiri, Sara, Puniya, Bhanwar, Naldi, Aurelien, Helikar, Tomas, Singh, Vidisha, Farinas Fernandez, Marco, Bermudez, Viviam, Tsirvouli, Eirini, Montagud, Arnau, Noel, Vincent, Ponce de Leon, Miguel, Maier, Dieter, Bauch, Angela, Gyori, Benjamin, Bachman, John, Luna, Agustin, Pinero, Janet, Furlong, Laura, Balaur, Irina, Rougny, Adrien, Jarosz, Yohan, Overall, Rupert, Phair, Robert, Perfetto, Livia, Matthews, Lisa, Rex, Devasahayam, Orlic-Milacic, Marija, Monraz Gomez, Luis, de Meulder, Bertrand, Ravel, Jean, Jassal, Bijay, Satagopam, Venkata, Wu, Guanming, Golebiewski, Martin, Gawron, Piotr, Calzone, Laurence, Beckmann, Jacques, Evelo, Chris, d'Eustachio, Peter, Schreiber, Falk, Saez-Rodriguez, Julio, Dopazo, Joaquin, Kuiper, Martin, Valencia, Alfonso, Wolkenhauer, Olaf, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Computational systems biology and optimization (Lifeware), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire de recherche européen pour la polyarthrite rhumatoïde (GenHotel), Université d'Évry-Val-d'Essonne (UEVE)-Université Paris-Saclay, University of Luxembourg [Luxembourg], Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris sciences et lettres (PSL), Maastricht Centre for Systems Biology [Maastricht] (MaCSBio), Maastricht University [Maastricht], Ontario Institute for Cancer Research [Canada] (OICR), Ontario Institute for Cancer Research, Keio University, Luxembourg Centre For Systems Biomedicine (LCSB), University of Konstanz, Hochschule Mittweida - University of Applied Sciences, Kanagawa Institute of Technology, Heidelberg University Hospital [Heidelberg], National Institute for Infectious Diseases 'Lazzaro Spallanzani', Hospital Universitario Virgen del Rocío [Sevilla], Biomedicine Institute of Sevilla [Seville, Spain], University of Nebraska–Lincoln, University of Nebraska System, Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Harvard Medical School [Boston] (HMS), Universitat Pompeu Fabra [Barcelona] (UPF), National Institute of Advanced Industrial Science and Technology (AIST), Humboldt University Of Berlin, Integrative Bioinformatics Inc [Mountain View], Department of Informatics and System Sciences (Sapienza University of Rome), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), New York University Langone Medical Center (NYU Langone Medical Center), NYU System (NYU), Yenepoya University, Janet Piñero, Laura I. Furlong: IMI2-JU grants, resources which are composed of financial contributions from the European Union’s Horizon 2020 Research and Innovation Programme and EFPIA [GA: 777365 eTRANSAFE], and the EU H2020 Programme [GA:964537 RISKHUNT3R], Project 001-P-001647—Valorisation of EGA for Industry and Society funded by the European Regional Development Fund (ERDF) and Generalitat de Catalunya, and Institute of Health Carlos III (project IMPaCT-Data, exp. IMP/00019), co-funded by the European Union, European Regional Development Fund (ERDF, 'A way to make Europe').

Subjects
SARS-CoV-2, disease maps, systems biology, dynamic models, systems medicine, large-scale community effort, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], mechanistic models
Abstract

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdisciplinary, the project is collaborative and supports community standards, open access, and the FAIR data principles. The coordination of community work allowed for an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework links key molecules highlighted from broad omics data analysis and computational modeling to dysregulated pathways in a cell-, tissue- or patient-specific manner. We also employ text mining and AI-assisted analysis to identify potential drugs and drug targets and use topological analysis to reveal interesting structural features of the map. The proposed framework is versatile and expandable, offering a significant upgrade in the arsenal used to understand virus-host interactions and other complex pathologies.

Published
2022

23. Pipeline Scheduling with Input Port Constraints for an FPGA-Based Biochemical Simulator

Author

Ishimori, Tomoya, Yamada, Hideki, Shibata, Yuichiro, Osana, Yasunori, Yoshimi, Masato, Nishikawa, Yuri, Amano, Hideharu, Funahashi, Akira, Hiroi, Noriko, Oguri, Kiyoshi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Becker, Jürgen, editor, Woods, Roger, editor, Athanas, Peter, editor, and Morgan, Fearghal, editor

Published
2009
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25. SBML Models and MathSBML

Author

Shapiro, Bruce E., Finney, Andrew, Hucka, Michael, Bornstein, Benjamin, Funahashi, Akira, Jouraku, Akiya, Keating, Sarah M., Le Novère, Nicolas, Matthews, Joanne, Schilstra, Maria J., and Choi, Sangdun, editor

Published
2007
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27. BioSimulators: a central registry of simulation engines and services for recommending specific tools

Author

Shaikh, Bilal, primary, Smith, Lucian P, additional, Vasilescu, Dan, additional, Marupilla, Gnaneswara, additional, Wilson, Michael, additional, Agmon, Eran, additional, Agnew, Henry, additional, Andrews, Steven S, additional, Anwar, Azraf, additional, Beber, Moritz E, additional, Bergmann, Frank T, additional, Brooks, David, additional, Brusch, Lutz, additional, Calzone, Laurence, additional, Choi, Kiri, additional, Cooper, Joshua, additional, Detloff, John, additional, Drawert, Brian, additional, Dumontier, Michel, additional, Ermentrout, G Bard, additional, Faeder, James R, additional, Freiburger, Andrew P, additional, Fröhlich, Fabian, additional, Funahashi, Akira, additional, Garny, Alan, additional, Gennari, John H, additional, Gleeson, Padraig, additional, Goelzer, Anne, additional, Haiman, Zachary, additional, Hasenauer, Jan, additional, Hellerstein, Joseph L, additional, Hermjakob, Henning, additional, Hoops, Stefan, additional, Ison, Jon C, additional, Jahn, Diego, additional, Jakubowski, Henry V, additional, Jordan, Ryann, additional, Kalaš, Matúš, additional, König, Matthias, additional, Liebermeister, Wolfram, additional, Sheriff, Rahuman S Malik, additional, Mandal, Synchon, additional, McDougal, Robert, additional, Medley, J Kyle, additional, Mendes, Pedro, additional, Müller, Robert, additional, Myers, Chris J, additional, Naldi, Aurelien, additional, Nguyen, Tung V N, additional, Nickerson, David P, additional, Olivier, Brett G, additional, Patoliya, Drashti, additional, Paulevé, Loïc, additional, Petzold, Linda R, additional, Priya, Ankita, additional, Rampadarath, Anand K, additional, Rohwer, Johann M, additional, Saglam, Ali S, additional, Singh, Dilawar, additional, Sinha, Ankur, additional, Snoep, Jacky, additional, Sorby, Hugh, additional, Spangler, Ryan, additional, Starruß, Jörn, additional, Thomas, Payton J, additional, van Niekerk, David, additional, Weindl, Daniel, additional, Zhang, Fengkai, additional, Zhukova, Anna, additional, Goldberg, Arthur P, additional, Schaff, James C, additional, Blinov, Michael L, additional, Sauro, Herbert M, additional, Moraru, Ion I, additional, and Karr, Jonathan R, additional

Published
2022
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28. Temperature elevation detection in migrating cells

Author

Nakamura, Takayuki, primary, Sakamoto, Joe, additional, Okabe, Kohki, additional, Taniguchi, Atsushi, additional, Yamada, Takahiro G., additional, Nonaka, Shigenori, additional, Kamei, Yasuhiro, additional, Funahashi, Akira, additional, Tominaga, Makoto, additional, and Hiroi, Noriko F., additional

Published
2022
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29. High quality genome assembly of the anhydrobiotic midge provides insights on a single chromosome-based emergence of extreme desiccation tolerance

Author

Yoshida, Yuki, primary, Shaikhutdinov, Nurislam, additional, Kozlova, Olga, additional, Itoh, Masayoshi, additional, Tagami, Michihira, additional, Murata, Mitsuyoshi, additional, Nishiyori-Sueki, Hiromi, additional, Kojima-Ishiyama, Miki, additional, Noma, Shohei, additional, Cherkasov, Alexander, additional, Gazizova, Guzel, additional, Nasibullina, Aigul, additional, Deviatiiarov, Ruslan, additional, Shagimardanova, Elena, additional, Ryabova, Alina, additional, Yamaguchi, Katsushi, additional, Bino, Takahiro, additional, Shigenobu, Shuji, additional, Tokumoto, Shoko, additional, Miyata, Yugo, additional, Cornette, Richard, additional, Yamada, Takahiro G, additional, Funahashi, Akira, additional, Tomita, Masaru, additional, Gusev, Oleg, additional, and Kikawada, Takahiro, additional

Published
2022
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36. SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter Estimation of Systems Biology Models

Author

Budman, Hector, Yamada, Takahiro, Ii, Kaito, König, Matthias, Feierabend, Martina, Dräger, Andreas, Funahashi, Akira, Budman, Hector, Yamada, Takahiro, Ii, Kaito, König, Matthias, Feierabend, Martina, Dräger, Andreas, and Funahashi, Akira

Abstract

In systems biology, biological phenomena are often modeled by Ordinary Differential Equations (ODEs) and distributed in the de facto standard file format SBML. The primary analyses performed with such models are dynamic simulation, steady-state analysis, and parameter estimation. These methodologies are mathematically formalized, and libraries for such analyses have been published. Several tools exist to create, simulate, or visualize models encoded in SBML. However, setting up and establishing analysis environments is a crucial hurdle for non-modelers. Therefore, easy access to perform fundamental analyses of ODE models is a significant challenge. We developed SBMLWebApp, a web-based service to execute SBML-based simulation, steady-state analysis, and parameter estimation directly in the browser without the need for any setup or prior knowledge to address this issue. SBMLWebApp visualizes the result and numerical table of each analysis and provides a download of the results. SBMLWebApp allows users to select and analyze SBML models directly from the BioModels Database. Taken together, SBMLWebApp provides barrier-free access to an SBML analysis environment for simulation, steady-state analysis, and parameter estimation for SBML models. SBMLWebApp is implemented in Java™ based on an Apache Tomcat® web server using COPASI, the Systems Biology Simulation Core Library (SBSCL), and LibSBMLSim as simulation engines. SBMLWebApp is licensed under MIT with source code freely available. At the end of this article, the Data Availability Statement gives the internet links to the two websites to find the source code and run the program online., Peer Reviewed

Published
2021

37. COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms

Author

Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Gomez, Luis Cristobal Monraz, Somers, Julia, Hoch, Matti, Gupta, Shailendra Kumar, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Schreiber, Falk, Montagud, Arnau, de Leon, Miguel Ponce, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Draeger, Andreas, Renz, Alina, Naveez, Muhammad, Bocskei, Zsolt, Messina, Francesco, Boernigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gokce Yagmur, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Eijssen, Lars, Ehrhart, Friederike, Rex, Devasahayam Arokia Balaya, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Orlic-Milacic, Marija, Ribeiro, Andrea Senff, Rothfels, Karen, Shamovsky, Veronica, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vazquez, Miguel, Porras, Pablo, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, de Waard, Anita, Turei, Denes, Luna, Augustin, Babur, Ozgun, Soliman, Sylvain, Valdeolivas, Alberto, Esteban-Medina, Marina, Pena-Chilet, Maria, Rian, Kinza, Helikar, Tomas, Puniya, Bhanwar Lal, Modos, Dezso, Treveil, Agatha, Olbei, Marton, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurelien, Naldi, Aurelien, Noel, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Auge, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, D'Eustachio, Peter, Saez-Rodriguez, Julio, Dopazo, Joaquin, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Gomez, Luis Cristobal Monraz, Somers, Julia, Hoch, Matti, Gupta, Shailendra Kumar, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Schreiber, Falk, Montagud, Arnau, de Leon, Miguel Ponce, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Draeger, Andreas, Renz, Alina, Naveez, Muhammad, Bocskei, Zsolt, Messina, Francesco, Boernigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gokce Yagmur, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Eijssen, Lars, Ehrhart, Friederike, Rex, Devasahayam Arokia Balaya, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Orlic-Milacic, Marija, Ribeiro, Andrea Senff, Rothfels, Karen, Shamovsky, Veronica, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vazquez, Miguel, Porras, Pablo, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, de Waard, Anita, Turei, Denes, Luna, Augustin, Babur, Ozgun, Soliman, Sylvain, Valdeolivas, Alberto, Esteban-Medina, Marina, Pena-Chilet, Maria, Rian, Kinza, Helikar, Tomas, Puniya, Bhanwar Lal, Modos, Dezso, Treveil, Agatha, Olbei, Marton, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurelien, Naldi, Aurelien, Noel, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Auge, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, D'Eustachio, Peter, Saez-Rodriguez, Julio, Dopazo, Joaquin, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, and Schneider, Reinhard

Abstract

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Published
2021
Full Text
View/download PDF

38. COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Fonds National de la Recherche - FnR [sponsor], Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Kumar Gupta, Shailendra, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Schreiber, Falk, Montagud, Arnau, Ponce de Leon, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yağmur, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Eijssen, Lars, Ehrhart, Friederike, Rex, Devasahayam Arokia Balaya, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Orlic-Milacic, Marija, Senff Ribeiro, Andrea, Rothfels, Karen, Shamovsky, Veronica, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vazquez, Miguel, Porras, Pablo, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, de Waard, Anita, Turei, Denes, Luna, Augustin, Babur, Ozgun, Soliman, Sylvain, Valdeolivas, Alberto, Esteban-Medina, Marina, Peña-Chilet, Maria, Rian, Kinza, Helikar, Tomáš, Puniya, Bhanwar Lal, Modos, Dezso, Treveil, Agatha, Olbei, Marton, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurélien, Naldi, Aurélien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Augé, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, D'Eustachio, Peter, Saez-Rodriguez, Julio, Dopazo, Joaquin, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Fonds National de la Recherche - FnR [sponsor], Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Fobo, Gisela, Montrone, Corinna, Brauner, Barbara, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Kumar Gupta, Shailendra, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Schreiber, Falk, Montagud, Arnau, Ponce de Leon, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yağmur, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Eijssen, Lars, Ehrhart, Friederike, Rex, Devasahayam Arokia Balaya, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Orlic-Milacic, Marija, Senff Ribeiro, Andrea, Rothfels, Karen, Shamovsky, Veronica, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vazquez, Miguel, Porras, Pablo, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, de Waard, Anita, Turei, Denes, Luna, Augustin, Babur, Ozgun, Soliman, Sylvain, Valdeolivas, Alberto, Esteban-Medina, Marina, Peña-Chilet, Maria, Rian, Kinza, Helikar, Tomáš, Puniya, Bhanwar Lal, Modos, Dezso, Treveil, Agatha, Olbei, Marton, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurélien, Naldi, Aurélien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Augé, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, D'Eustachio, Peter, Saez-Rodriguez, Julio, Dopazo, Joaquin, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, and Schneider, Reinhard

Abstract

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Published
2021

39. COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

Author

Fonds National de la Recherche Luxembourg, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Science, Research and Art Baden-Württemberg, German Center for Infection Research, Netherlands Organisation for Health Research and Development, National Institutes of Health (US), European Molecular Biology Laboratory, Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Schreiber, Falk, Montagud, Arnau, Ponce de León, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Orlic-Milacic, Marija, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Senff Ribeiro, Andrea, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yagmu, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Rothfels, Karen, Eijssen, Lars, Ehrhart, Friederike, Arokia Balaya Rex, Devasahayam, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Shamovsky, Veronic, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Soliman, Sylvain, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Valdeolivas, Alberto, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vázquez, Miguel, Porras, Pablo, Esteban-Medina, Marina, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, Waard, Anita de, Turei, Denes, Luna, Augustín, Babur, Ozgun, Peña-Chilet, María, Rian, Kinza, Helikar, Tomas, Lal Puniya, Bhanwar, Modos, Dezso, Treveil, Agatha, Olbe, Marton, Fobo, Gisela, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurelien, Naldi, Aurelien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Montrone, Corinna, Auge, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L ., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, Brauner, Barbara, D’Eustachio, Peter, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Gupta, Shailendra Kumar, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias, Fonds National de la Recherche Luxembourg, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Science, Research and Art Baden-Württemberg, German Center for Infection Research, Netherlands Organisation for Health Research and Development, National Institutes of Health (US), European Molecular Biology Laboratory, Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Schreiber, Falk, Montagud, Arnau, Ponce de León, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Orlic-Milacic, Marija, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Senff Ribeiro, Andrea, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yagmu, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Rothfels, Karen, Eijssen, Lars, Ehrhart, Friederike, Arokia Balaya Rex, Devasahayam, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Shamovsky, Veronic, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Soliman, Sylvain, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Valdeolivas, Alberto, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vázquez, Miguel, Porras, Pablo, Esteban-Medina, Marina, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, Waard, Anita de, Turei, Denes, Luna, Augustín, Babur, Ozgun, Peña-Chilet, María, Rian, Kinza, Helikar, Tomas, Lal Puniya, Bhanwar, Modos, Dezso, Treveil, Agatha, Olbe, Marton, Fobo, Gisela, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurelien, Naldi, Aurelien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Montrone, Corinna, Auge, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L ., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, Brauner, Barbara, D’Eustachio, Peter, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Gupta, Shailendra Kumar, Scheel, Julia, Borlinghaus, Hanna, and Czauderna, Tobias

Abstract

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Published
2021

40. Genome-Wide Role of HSF1 in Transcriptional Regulation of Desiccation Tolerance in the Anhydrobiotic Cell Line, Pv11

Author

Tokumoto, Shoko, primary, Miyata, Yugo, additional, Deviatiiarov, Ruslan, additional, Yamada, Takahiro G., additional, Hiki, Yusuke, additional, Kozlova, Olga, additional, Yoshida, Yuki, additional, Cornette, Richard, additional, Funahashi, Akira, additional, Shagimardanova, Elena, additional, Gusev, Oleg, additional, and Kikawada, Takahiro, additional

Published
2021
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41. Practical implementation of a network-based Stochastic biochemical simulation system on an FPGA

Author

Yoshimi, Masato, Nishikawa, Yuri, Osana, Yasunori, Funahashi, Akira, Hiroi, Noriko, Shibata, Yuichiro, Yamada, Hideki, Kitano, Hiroaki, Amano, Hideharu, Yoshimi, Masato, Nishikawa, Yuri, Osana, Yasunori, Funahashi, Akira, Hiroi, Noriko, Shibata, Yuichiro, Yamada, Hideki, Kitano, Hiroaki, and Amano, Hideharu

Abstract

Stochastic simulation of biochemical reaction networks are widely focused by life scientists to represent stochastic behaviors in cellular processes. Stochastic algorithm has loop-and thread-level parallelism, and it is suitable for running on application specific hardware to achieve high performance with low cost. We have implemented and evaluated the FPGA-based stochastic simulator according to theoretical research of the algorithm. This paper introduces an improved architecture for accelerating a stochastic simulation algorithm called the Next Reaction Method. This new architecture has scalability to various size of FPGA. As the result with a middle-range FPGA, 5.38 times higher throughput was obtained compared to software running on a Core 2 Quad Q6600 2.40GHz., 2008 International Conference on Field Programmable Logic and Applications, FPL; Heidelberg; 8 September 2008 through 10 September 2008, identifier:2008 International Conference on Field Programmable Logic and Applications, pp.663-666

Published
2020

42. SBML Level 3: an extensible format for the exchange and reuse of biological models

Author

Computer Science, Keating, Sarah M., Waltemath, Dagmar, Koenig, Matthias, Zhang, Fengkai, Draeger, Andreas, Chaouiya, Claudine, Bergmann, Frank T., Finney, Andrew, Gillespie, Colin S., Helikar, Tomas, Hoops, Stefan, Malik-Sheriff, Rahuman S., Moodie, Stuart L., Moraru, Ion I., Myers, Chris J., Naldi, Aurelien, Olivier, Brett G., Sahle, Sven, Schaff, James C., Smith, Lucian P., Swat, Maciej J., Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J., Blinov, Michael L., Begley, Kimberly, Faeder, James R., Gomez, Harold F., Hamm, Thomas M., Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L., Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J., Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A., Shapiro, Bruce E., Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M., Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C., Hucka, Michael, Computer Science, Keating, Sarah M., Waltemath, Dagmar, Koenig, Matthias, Zhang, Fengkai, Draeger, Andreas, Chaouiya, Claudine, Bergmann, Frank T., Finney, Andrew, Gillespie, Colin S., Helikar, Tomas, Hoops, Stefan, Malik-Sheriff, Rahuman S., Moodie, Stuart L., Moraru, Ion I., Myers, Chris J., Naldi, Aurelien, Olivier, Brett G., Sahle, Sven, Schaff, James C., Smith, Lucian P., Swat, Maciej J., Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J., Blinov, Michael L., Begley, Kimberly, Faeder, James R., Gomez, Harold F., Hamm, Thomas M., Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L., Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J., Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A., Shapiro, Bruce E., Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M., Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C., and Hucka, Michael

Abstract

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developedSBMLLevel 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades ofSBMLand a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and howSBMLLevel 3 provides the foundation needed to support this evolution.

Published
2020

44. Control and measurement of nano/micro-space temperature that changes cellular behavior

Author

Nakamura, Takayuki, primary, Saito, Takaya, additional, Tanimoto, Ryuichi, additional, Yamada, Takahiro, additional, Funahashi, Akira, additional, Taniguchi, Atsushi, additional, Nonaka, Shigenori, additional, Sakamoto, Joe, additional, Kamei, Yasuhiro, additional, Tominaga, Makoto, additional, Okabe, Kohki, additional, Yanase, Yuki, additional, Kishi, Hiroko, additional, and Hiroi, Noriko F., additional

Published
2021
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47. Software support for SBGN maps: SBGN-ML and LibSBGN

Author

van Iersel, Martijn P., Villéger, Alice C., Czauderna, Tobias, Boyd, Sarah E., Bergmann, Frank T., Luna, Augustin, Demir, Emek, Sorokin, Anatoly, Dogrusoz, Ugur, Matsuoka, Yukiko, Funahashi, Akira, Aladjem, Mirit I., Mi, Huaiyu, Moodie, Stuart L., Kitano, Hiroaki, Le Novère, Nicolas, and Schreiber, Falk

Published
2012
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49. Cas9-mediated Genome Editing Reveals a Significant Contribution of Calcium Signaling Pathways to Anhydrobiosis in Pv11

Author

Miyata, Yugo, primary, Fuse, Hiroto, additional, Tokumoto, Shoko, additional, Hiki, Yusuke, additional, Deviatiiarov, Ruslan, additional, Yoshida, Yuki, additional, Yamada, Takahiro G., additional, Cornette, Richard, additional, Gusev, Oleg, additional, Shagimardanova, Elena, additional, Funahashi, Akira, additional, and Kikawada, Takahiro, additional

Published
2020
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