Publications

56 Publications visible to you, out of a total of 56

Abstract (Expand)

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Authors: M. L. Neal, M. Konig, D. Nickerson, G. Misirli, R. Kalbasi, A. Drager, K. Atalag, V. Chelliah, M. T. Cooling, D. L. Cook, S. Crook, M. de Alba, S. H. Friedman, A. Garny, J. H. Gennari, P. Gleeson, M. Golebiewski, M. Hucka, N. Juty, C. Myers, B. G. Olivier, H. M. Sauro, M. Scharm, J. L. Snoep, V. Toure, A. Wipat, O. Wolkenhauer, D. Waltemath

Date Published: 22nd Mar 2019

InBook: Not specified

Abstract (Expand)

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Authors: M. L. Neal, M. Konig, D. Nickerson, G. Misirli, R. Kalbasi, A. Drager, K. Atalag, V. Chelliah, M. T. Cooling, D. L. Cook, S. Crook, M. de Alba, S. H. Friedman, A. Garny, J. H. Gennari, P. Gleeson, M. Golebiewski, M. Hucka, N. Juty, C. Myers, B. G. Olivier, H. M. Sauro, M. Scharm, J. L. Snoep, V. Toure, A. Wipat, O. Wolkenhauer, D. Waltemath

Date Published: 22nd Mar 2019

Book: Brief Bioinform

Abstract (Expand)

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Authors: M. L. Neal, M. Konig, D. Nickerson, G. Misirli, R. Kalbasi, A. Drager, K. Atalag, V. Chelliah, M. T. Cooling, D. L. Cook, S. Crook, M. de Alba, S. H. Friedman, A. Garny, J. H. Gennari, P. Gleeson, M. Golebiewski, M. Hucka, N. Juty, C. Myers, B. G. Olivier, H. M. Sauro, M. Scharm, J. L. Snoep, V. Toure, A. Wipat, O. Wolkenhauer, D. Waltemath

Date Published: 22nd Mar 2019

Booklet: Brief Bioinform

Abstract

Not specified

Author: Alan Williams

Date Published: 16th Jan 2019

Journal: Not specified

Abstract

Not specified

Authors: Sebastian Schmelzle, Thomas van de Kamp, Michael Heethoff, Vincent Heuveline, Philipp Lösel, Jürgen Becker, Felix Beckmann, Frank Schluenzen, Jörg U. Hammel, Andreas Kopmann, Wolfgang Mexner, Matthias Vogelgesang, Nicholas T. Jerome, Oliver Betz, Rolf Beutel, Benjamin Wipfler, Alexander Blanke, Steffen Harzsch, Marie Hörnig, Tilo Baumbach

Date Published: 7th Sep 2017

Journal: Developments in X-Ray Tomography XI

Abstract

Not specified

Author: Wolfgang Müller

Date Published: 2017

Journal: Research and Advanced Technology for Digital Libraries

Abstract

Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate comprehensive models of complex cells.

Authors: Dagmar Waltemath, Jonathan R Karr, Frank T Bergmann, Vijayalakshmi Chelliah, Michael Hucka, Marcus Krantz, Wolfram Liebermeister, Pedro Mendes, Chris J Myers, Pinar Pir, Begum Alaybeyoglu, Naveen K Aranganathan, Kambiz Baghalian, Arne T Bittig, Paulo E Pinto Burke, Matteo Cantarelli, Yin Hoon Chew, Rafael S Costa, Joseph Cursons, Tobias Czauderna, Arthur P Goldberg, Harold F Gomez, Jens Hahn, Tuure Hameri, Daniel F Hernandez Gardiol, Denis Kazakiewicz, Ilya Kiselev, Vincent Knight-Schrijver, Christian Knupfer, Matthias Konig, Daewon Lee, Audald Lloret-Villas, Nikita Mandrik, J Kyle Medley, Bertrand Moreau, Hojjat Naderi-Meshkin, Sucheendra K Palaniappan, Daniel Priego-Espinosa, Martin Scharm, Mahesh Sharma, Kieran Smallbone, Natalie Stanford, Je-Hoon Song, Tom Theile, Milenko Tokic, Namrata Tomar, Vasundra Toure, Jannis Uhlendorf, Thawfeek M Varusai, Leandro H Watanabe, Florian Wendland, Markus Wolfien, James T Yurkovich, Yan Zhu, Argyris Zardilis, Anna Zhukova, Falk Schreiber

Date Published: 24th Sep 2016

Journal: IEEE transactions on bio-medical engineering

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