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19 Publications visible to you, out of a total of 19
PK-DB: pharmacokinetics database for individualized and stratified computational modeling.

Abstract (Expand)

A multitude of pharmacokinetics studies have been published. However, due to the lack of an open database, pharmacokinetics data, as well as the corresponding meta-information, have been difficult to … access. We present PK-DB (https://pk-db.com), an open database for pharmacokinetics information from clinical trials. PK-DB provides curated information on (i) characteristics of studied patient cohorts and subjects (e.g. age, bodyweight, smoking status, genetic variants); (ii) applied interventions (e.g. dosing, substance, route of application); (iii) pharmacokinetic parameters (e.g. clearance, half-life, area under the curve) and (iv) measured pharmacokinetic time-courses. Key features are the representation of experimental errors, the normalization of measurement units, annotation of information to biological ontologies, calculation of pharmacokinetic parameters from concentration-time profiles, a workflow for collaborative data curation, strong validation rules on the data, computational access via a REST API as well as human access via a web interface. PK-DB enables meta-analysis based on data from multiple studies and data integration with computational models. A special focus lies on meta-data relevant for individualized and stratified computational modeling with methods like physiologically based pharmacokinetic (PBPK), pharmacokinetic/pharmacodynamic (PK/PD), or population pharmacokinetic (pop PK) modeling.

Authors: J. Grzegorzewski, J. Brandhorst, K. Green, D. Eleftheriadou, Y. Duport, F. Barthorscht, A. Koller, D. Y. J. Ke, S. De Angelis, M. Konig

Date Published: 5th Nov 2020

Publication Type: Journal

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

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

Model Order Reduction (MOR) of Function‐Perfusion‐Growth Simulation in the Human Fatty Liver via Artificial Neural Network (ANN)

Abstract (Expand)

Numerical modeling of biological systems has become an important assistance for understanding and predicting hepatic diseases like non‐alcoholic fatty liver disease (NAFLD) or the detoxification of … drugs and toxines by the liver. We developed a model for the simulation of hepatic function‐perfusion processes using a multiscale and multiphase approach. Here, the liver lobules are described using a homogenization approach with a coupled set of partial differential equations (PDE) based on the Theory of Porous Media (TPM) to describe the coupled blood transport and tissue deformation. For the description of metabolic processes on cellular scale ordinary differential equations (ODE) are used. For many practical and clinical applications, e.g. optimization procedures or uncertainty quantification, a fast but reliable computation is required. Thus, we use a non‐linear model order reduction (MOR) based on an artificial neural network (ANN) for the prediction of simulation results. The practicability of this approach is shown in a comparison between the high fidelity numerical simulation of a NAFLD and the predicted results by the ANN.

Authors: Lena Lambers, Tim Ricken, Matthias König

Date Published: 1st Nov 2019

Publication Type: Journal

PK-DB: PharmacoKinetics DataBase for Individualized and Stratified Computational Modeling

Abstract (Expand)

A multitude of pharmacokinetics studies have been published. However, due to the lack of an open database, pharmacokinetics data, as well as the corresponding meta-information, have been difficult to … access. We present PK-DB (https://pk-db.com), an open database for pharmacokinetics information from clinical trials including pre-clinical research. PK-DB provides curated information on (i) characteristics of studied patient cohorts and subjects (e.g. age, bodyweight, smoking status); (ii) applied interventions (e.g. dosing, substance, route of application); (iii) measured pharmacokinetic time-courses; (iv) pharmacokinetic parameters (e.g. clearance, half-life, area under the curve). Key features are the representation of experimental errors, the normalization of measurement units, annotation of information to biological ontologies, calculation of pharmacokinetic parameters from concentration-time profiles, a workflow for collaborative data curation, strong validation rules on the data, computational access via a REST API as well as human access via a web interface. PK-DB enables meta-analysis based on data from multiple studies and data integration with computational models. A special focus lies on meta-data relevant for individualized and stratified computational modeling with methods like physiologically based pharmacokinetic (PBPK), pharmacokinetic/pharmacodynamic (PK/DB), or population pharmacokinetic (pop PK) modeling.

Authors: Jan Grzegorzewski, Janosch Brandhorst, Dimitra Eleftheriadou, Kathleen Green, Matthias König

Date Published: 9th Sep 2019

Publication Type: Unpublished

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2019

Abstract (Expand)

This special issue of the Journal of Integrative Bioinformatics presents an overview of COMBINE standards and their latest specifications. The standards cover representation formats for computational … modeling in synthetic and systems biology and include BioPAX, CellML, NeuroML, SBML, SBGN, SBOL and SED-ML. The articles in this issue contain updated specifications of SBGN Process Description Level 1 Version 2, SBML Level 3 Core Version 2 Release 2, SBOL Version 2.3.0, and SBOL Visual Version 2.1.

Authors: Falk Schreiber, Björn Sommer, Gary D. Bader, Padraig Gleeson, Martin Golebiewski, Michael Hucka, Sarah M. Keating, Matthias König, Chris Myers, David Nickerson, Dagmar Waltemath

Date Published: 26th Jun 2019

Publication Type: Not specified

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

Harmonizing semantic annotations for computational models in biology.

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 Jan 2018

Publication Type: Not specified

Computational Modeling in Liver Surgery

Abstract (Expand)

The need for extended liver resection is increasing due to the growing incidence of liver tumors in aging societies. Individualized surgical planning is the key for identifying the optimal resection … strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery.

Authors: Bruno Christ, Uta Dahmen, Karl-Heinz Herrmann, Matthias König, Jürgen R. Reichenbach, Tim Ricken, Jana Schleicher, Lars Ole Schwen, Sebastian Vlaic, Navina Waschinsky

Date Published: 14th Nov 2017

Publication Type: Not specified

Toward Community Standards and Software for Whole-Cell Modeling.

Abstract (Expand)

OBJECTIVE: 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. … METHODS: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in the Systems Biology Markup Language. RESULTS: Our analysis revealed several challenges to representing WC models using the current standards. CONCLUSION: We, therefore, propose several new WC modeling standards, software, and databases. SIGNIFICANCE: We anticipate that these new standards and software will enable more comprehensive models.

Authors: D. Waltemath, J. R. Karr, F. T. Bergmann, V. Chelliah, M. Hucka, M. Krantz, W. Liebermeister, P. Mendes, C. J. Myers, P. Pir, B. Alaybeyoglu, N. K. Aranganathan, K. Baghalian, A. T. Bittig, P. E. Burke, M. Cantarelli, Y. H. Chew, R. S. Costa, J. Cursons, T. Czauderna, A. P. Goldberg, H. F. Gomez, J. Hahn, T. Hameri, D. F. Gardiol, D. Kazakiewicz, I. Kiselev, V. Knight-Schrijver, C. Knupfer, M. Konig, D. Lee, A. Lloret-Villas, N. Mandrik, J. K. Medley, B. Moreau, H. Naderi-Meshkin, S. K. Palaniappan, D. Priego-Espinosa, M. Scharm, M. Sharma, K. Smallbone, N. J. Stanford, J. H. Song, T. Theile, M. Tokic, N. Tomar, V. Toure, J. Uhlendorf, T. M. Varusai, L. H. Watanabe, F. Wendland, M. Wolfien, J. T. Yurkovich, Y. Zhu, A. Zardilis, A. Zhukova, F. Schreiber

Date Published: 10th Jun 2016

Publication Type: Not specified

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