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14 Publications visible to you, out of a total of 14
Systems Biology Markup Language (SBML) Level 3 Package: Distributions, Version 1, Release 1.

Abstract (Expand)

Biological models often contain elements that have inexact numerical values, since they are based on values that are stochastic in nature or data that contains uncertainty. The Systems Biology Markup … Language (SBML) Level 3 Core specification does not include an explicit mechanism to include inexact or stochastic values in a model, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactic constructs. The SBML Distributions package for SBML Level 3 adds the necessary features to allow models to encode information about the distribution and uncertainty of values underlying a quantity.

Authors: Lucian P. Smith, Stuart L. Moodie, Frank T. Bergmann, Colin Gillespie, Sarah M. Keating, Matthias König, Chris J. Myers, Maciek J. Swat, Darren J. Wilkinson, Michael Hucka

Date Published: 1st Aug 2020

Publication Type: Journal

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

Abstract (Expand)

Systems biology has experienced dramatic growth in the number, size and complexity of computational models describing biology. To reproduce simulation results and reuse models, researchers need to … exchange precise and unambiguous descriptions of model structure and meaning. SBML (the Systems Biology Markup Language) is a community-developed format for this purpose. The latest edition, called SBML Level 3, has a modular structure, with a core suited to representing reaction-based models, and packages that extend the core with features suited for a variety of model types. Examples include constraint-based models, reaction-diffusion models, logical network models, and rule-based models. SBML and its rich software ecosystem have transformed the way systems biologists build and interact with models, and has played an important role in increasing model interoperability and reuse over the past two decades. More recently, a rise of multiscale models of whole cells and organs, and new data sources such as single cells measurements and live imaging, have precipitated new ways of integrating data and models. SBML Level 3 provides the foundation needed to support this evolution.

Authors: SM Keating, D Waltemath, M König, F Zhang, A Dräger, C Chaouiya, FT Bergmann, A Finney, CS Gillespie, T Helikar, S Hoops, RS Malik-Sheriff, SL Moodie, II Moraru, CJ Myers, A Naldi, BG Olivier, S Sahle, JC Schaff, LP Smith, MJ Swat, DT, L Watanabe, DJ Wilkinson, ML Blinov, K Begley, JR Faeder, HF Gómez, TM Hamm, Y Inagaki, W Liebermeister, AL Lister, D Lucio, E Mjolsness, CJ Proctor, K Raman, N Rodriguez, CA Shaffer, BE Shapiro, J Stelling, N Swainston, N Tanimura, J Wagner, M Meier-Schellersheim, HM Sauro, B Palsson, H Bolouri, H Kitano, Akira Funahashi, H Hermjakob, JC Doyle, M Hucka, SBML Community members

Date Published: 1st Jul 2020

Publication Type: Journal

matthiaskoenig/sbmlsim: sbmlsim-v0.1.3: SBML simulation made easy

Abstract

sbmlsim: Python utilities for simulating SBML models available at https://github.com/matthiaskoenig/sbmlsim.

Author: Matthias König

Date Published: 1st Jul 2020

Publication Type: Misc

The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE)

Abstract (Expand)

This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together … researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.

Authors: Dagmar Waltemath, Martin Golebiewski, Michael L Blinov, Padraig Gleeson, Henning Hermjakob, Michael Hucka, Esther Thea Inau, Sarah M Keating, Matthias König, Olga Krebs, Rahuman S Malik-Sheriff, David Nickerson, Ernst Oberortner, Herbert M Sauro, Falk Schreiber, Lucian Smith, Melanie I Stefan, Ulrike Wittig, Chris J Myers

Date Published: 29th Jun 2020

Publication Type: Journal

matthiaskoenig/pkdb: PKDB-v0.8.0 - pharmacokinetics database

Abstract (Expand)

PK-DB is a database and web interface for pharmacokinetics data and information from clinical trials as well as pre-clinical research. PK-DB allows to curate pharmacokinetics data integrated with the … corresponding meta-information. PK-DB is available at https://pk-db.com

Authors: Matthias König, Jan Grzegorzewski

Date Published: 1st Jun 2020

Publication Type: Misc

MEMOTE for standardized genome-scale metabolic model testing.

Abstract

Not specified

Authors: C. Lieven, M. E. Beber, B. G. Olivier, F. T. Bergmann, M. Ataman, P. Babaei, J. A. Bartell, L. M. Blank, S. Chauhan, K. Correia, C. Diener, A. Drager, B. E. Ebert, J. N. Edirisinghe, J. P. Faria, A. M. Feist, G. Fengos, R. M. T. Fleming, B. Garcia-Jimenez, V. Hatzimanikatis, W. van Helvoirt, C. S. Henry, H. Hermjakob, M. J. Herrgard, A. Kaafarani, H. U. Kim, Z. King, S. Klamt, E. Klipp, J. J. Koehorst, M. Konig, M. Lakshmanan, D. Y. Lee, S. Y. Lee, S. Lee, N. E. Lewis, F. Liu, H. Ma, D. Machado, R. Mahadevan, P. Maia, A. Mardinoglu, G. L. Medlock, J. M. Monk, J. Nielsen, L. K. Nielsen, J. Nogales, I. Nookaew, B. O. Palsson, J. A. Papin, K. R. Patil, M. Poolman, N. D. Price, O. Resendis-Antonio, A. Richelle, I. Rocha, B. J. Sanchez, P. J. Schaap, R. S. Malik Sheriff, S. Shoaie, N. Sonnenschein, B. Teusink, P. Vilaca, J. O. Vik, J. A. H. Wodke, J. C. Xavier, Q. Yuan, M. Zakhartsev, C. Zhang

Date Published: 4th Mar 2020

Publication Type: Journal

matthiaskoenig/sbmlutils: sbmlutils-v0.3.9: python utilities for SBML

Abstract

sbmlutils is a collection of python utilities for working with SBML models implemented on top of libSBML and other libraries available from https://github.com/matthiaskoenig/sbmlutils

Author: Matthias König

Date Published: 1st Mar 2020

Publication Type: Misc

Executable Simulation Model of the Liver

Abstract (Expand)

To address the issue of reproducibility in computational modeling we developed the concept of an executable simulation model (EXSIMO). An EXSIMO combines model, data and code with the execution environment … to run the computational analysis in an automated manner using tools from software engineering. Key components are i) models, data and code for the computational analysis; ii) tests for models, data and code; and iii) an automation layer to run tests and execute the analysis. An EXSIMO combines version control, model, data, units, annotations, analysis, reports, execution environment, testing, continuous integration and release. We applied the concept to perform a replication study of a computational analysis of hepatic glucose metabolism in the liver. The corresponding EXSIMO is available from https://github.com/matthiaskoenig/exsimo.

Author: Matthias König

Date Published: 6th Jan 2020

Publication Type: Unpublished

matthiaskoenig/exsimo: exsimo-v0.3.2 - EXecutable SImulation MOdels

Abstract (Expand)

EXSIMO: EXecutable SImulation MOdel; Data, model and code for executable simulation model of hepatic glucose metabolism Reports: https://matthiaskoenig.github.io/exsimo/ Docker images: …: https://hub.docker.com/r/matthiaskoenig/exsimo Github releases: https://github.com/matthiaskoenig/exsimo/releases

Author: Matthias König

Date Published: 2020

Publication Type: Misc

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core Release 2.

Abstract (Expand)

Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing … computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Release 2 of Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. Release 2 corrects some errors and clarifies some ambiguities discovered in Release 1. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project website at http://sbml.org/.

Authors: M. Hucka, F. T. Bergmann, C. Chaouiya, A. Drager, S. Hoops, S. M. Keating, M. Konig, N. L. Novere, C. J. Myers, B. G. Olivier, S. Sahle, J. C. Schaff, R. Sheriff, L. P. Smith, D. Waltemath, D. J. Wilkinson, F. Zhang

Date Published: 20th Jun 2019

Publication Type: Not specified

Tellurium: An extensible python-based modeling environment for systems and synthetic biology.

Abstract (Expand)

Here we present Tellurium, a Python-based environment for model building, simulation, and analysis that facilitates reproducibility of models in systems and synthetic biology. Tellurium is a modular, … cross-platform, and open-source simulation environment composed of multiple libraries, plugins, and specialized modules and methods. Tellurium is a self-contained modeling platform which comes with a fully configured Python distribution. Two interfaces are provided, one based on the Spyder IDE which has an accessible user interface akin to MATLAB and a second based on the Jupyter Notebook, which is a format that contains live code, equations, visualizations, and narrative text. Tellurium uses libRoadRunner as the default SBML simulation engine which supports deterministic simulations, stochastic simulations, and steady-state analyses. Tellurium also includes Antimony, a human-readable model definition language which can be converted to and from SBML. Other standard Python scientific libraries such as NumPy, SciPy, and matplotlib are included by default. Additionally, we include several user-friendly plugins and advanced modules for a wide-variety of applications, ranging from complex algorithms for bifurcation analysis to multidimensional parameter scanning. By combining multiple libraries, plugins, and modules into a single package, Tellurium provides a unified but extensible solution for biological modeling and analysis for both novices and experts. AVAILABILITY: tellurium.analogmachine.org.

Authors: K. Choi, J. K. Medley, M. Konig, K. Stocking, L. Smith, S. Gu, H. M. Sauro

Date Published: 28th Jul 2018

Publication Type: Not specified

Tellurium notebooks-An environment for reproducible dynamical modeling in systems biology.

Abstract (Expand)

The considerable difficulty encountered in reproducing the results of published dynamical models limits validation, exploration and reuse of this increasingly large biomedical research resource. To … address this problem, we have developed Tellurium Notebook, a software system for model authoring, simulation, and teaching that facilitates building reproducible dynamical models and reusing models by 1) providing a notebook environment which allows models, Python code, and narrative to be intermixed, 2) supporting the COMBINE archive format during model development for capturing model information in an exchangeable format and 3) enabling users to easily simulate and edit public COMBINE-compliant models from public repositories to facilitate studying model dynamics, variants and test cases. Tellurium Notebook, a Python-based Jupyter-like environment, is designed to seamlessly inter-operate with these community standards by automating conversion between COMBINE standards formulations and corresponding in-line, human-readable representations. Thus, Tellurium brings to systems biology the strategy used by other literate notebook systems such as Mathematica. These capabilities allow users to edit every aspect of the standards-compliant models and simulations, run the simulations in-line, and re-export to standard formats. We provide several use cases illustrating the advantages of our approach and how it allows development and reuse of models without requiring technical knowledge of standards. Adoption of Tellurium should accelerate model development, reproducibility and reuse.

Authors: J. K. Medley, K. Choi, M. Konig, L. Smith, S. Gu, J. Hellerstein, S. C. Sealfon, H. M. Sauro

Date Published: 16th Jun 2018

Publication Type: Not specified

Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3).

Abstract (Expand)

The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML … standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment.

Authors: F. T. Bergmann, J. Cooper, M. Konig, I. Moraru, D. Nickerson, N. Le Novere, B. G. Olivier, S. Sahle, L. Smith, D. Waltemath

Date Published: 20th Mar 2018

Publication Type: Not specified

A brief history of COMBINE

Abstract (Expand)

Standards for data exchange are critical to the development of any field. They enable researchers and practitioners to transport information reliably, to apply a variety of tools to their problems, and … to reproduce scientific results. Over the past two decades, a range of standards have been developed to facilitate the exchange and reuse of information in the domain of representation and modeling of biological systems. These standards are complementary, so the interactions between their developers increased over time. By the end of the last decade, the community of researchers decided that more interoperability is required between the standards, and that common development is needed to make better use of effort, time, and money devoted to this activity. The COmputational MOdeling in Biology NEtwork (COMBINE) was created to enable the sharing of resources, tools, and other infrastructure. This paper provides a brief history of this endeavor and the challenges that remain.

Authors: Chris J. Myers, Gary Bader, Padraig Gleeson, Martin Golebiewski, Michael Hucka, Nicolas Le Novere, David P. Nickerson, Falk Schreiber, Dagmar Waltemath

Date Published: 1st Dec 2017

Publication Type: Not specified

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