FitMultiCell: simulating and parameterizing computational models of multi-scale and multi-cellular processes.

Abstract (Expand)

MOTIVATION: Biological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyse and understand the processes determining tissue dynamics. These models usually depend … on parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as approximate Bayesian computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes. RESULTS: Here, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology. AVAILABILITY AND IMPLEMENTATION: FitMultiCell is available open-source at https://gitlab.com/fitmulticell/fit.

Authors: E. Alamoudi, Y. Schalte, R. Muller, J. Starruss, N. Bundgaard, F. Graw, L. Brusch, J. Hasenauer

Date Published: 1st Nov 2023

Publication Type: Journal

Towards standardization guidelines for in silico approaches in personalized medicine.

Abstract (Expand)

Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind … its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stakeholder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine.

Authors: S. Brunak, C. Bjerre Collin, K. Eva O Cathaoir, M. Golebiewski, M. Kirschner, I. Kockum, H. Moser, D. Waltemath

Date Published: 24th Jul 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

Open modeling and exchange (OMEX) metadata specification version 1.0

Abstract (Expand)

A standardized approach to annotating computational biomedical models and their associated files can facilitate model reuse and reproducibility among research groups, enhance search and retrieval of … models and data, and enable semantic comparisons between models. Motivated by these potential benefits and guided by consensus across the COmputational Modeling in BIology NEtwork (COMBINE) community, we have developed a specification for encoding annotations in Open Modeling and EXchange (OMEX)-formatted archives. Distributing modeling projects within these archives is a best practice established by COMBINE, and the OMEX metadata specification presented here provides a harmonized, community-driven approach for annotating a variety of standardized model and data representation formats within an archive. The specification primarily includes technical guidelines for encoding archive metadata, so that software tools can more easily utilize and exchange it, thereby spurring broad advancements in model reuse, discovery, and semantic analyses.

Authors: Maxwell L. Neal, John H. Gennari, Dagmar Waltemath, David P. Nickerson, Matthias König

Date Published: 25th Jun 2020

Publication Type: Journal

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

Data Formats for Systems Biology and Quantitative Modeling

Abstract (Expand)

Data standards support the reliable exchange of information, the interoperability of tools, and the reproducibility of scientific results. In systems biology standards are agreed ways of structuring, … describing, and associating models and data, as well as their respective parts, graphical visualization, and information about applied experimental or computational methods. Such standards also assist with describing how constituent parts interact together, or are linked, and how they are embedded in their environmental and experimental context. Here the focus will be on standards for formatting models and their content, and on metadata checklists and ontologies that support modeling.

Author: Martin Golebiewski

Date Published: 2019

Publication Type: InBook

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

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

The Human Physiome: how standards, software and innovative service infrastructures are providing the building blocks to make it achievable

Abstract (Expand)

Reconstructing and understanding the Human Physiome virtually is a complex mathematical problem, and a highly demanding computational challenge. Mathematical models spanning from the molecular level … through to whole populations of individuals must be integrated, then personalized. This requires interoperability with multiple disparate and geographically separated data sources, and myriad computational software tools. Extracting and producing knowledge from such sources, even when the databases and software are readily available, is a challenging task. Despite the difficulties, researchers must frequently perform these tasks so that available knowledge can be continually integrated into the common framework required to realize the Human Physiome. Software and infrastructures that support the communities that generate these, together with their underlying standards to format, describe and interlink the corresponding data and computer models, are pivotal to the Human Physiome being realized. They provide the foundations for integrating, exchanging and re-using data and models efficiently, and correctly, while also supporting the dissemination of growing knowledge in these forms. In this paper, we explore the standards, software tooling, repositories and infrastructures that support this work, and detail what makes them vital to realizing the Human Physiome.

Authors: D. Nickerson, K. Atalag, B. de Bono, J. Geiger, C. Goble, S. Hollmann, J. Lonien, W. Muller, B. Regierer, N. J. Stanford, M. Golebiewski, P. Hunter

Date Published: 7th Apr 2016

Publication Type: Not specified

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016

Abstract (Expand)

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special … issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them.

Authors: F. Schreiber, G. D. Bader, P. Gleeson, M. Golebiewski, M. Hucka, N. Le Novere, C. Myers, D. Nickerson, B. Sommer, D. Walthemath

Date Published: 12th Feb 2017

Publication Type: Not specified

Integration of Representative Sinusoids into a Physiologically Based Whole-Body Model for a Detailed Description of Biliary Transport

Poster at SBMC 2018

Creators: Lars Ole Schwen, Lars Kuepfer, Ahmed Ghallab, Jan Hengstler, Tobias Preusser, Raymond Reif

Submitter: Lars Ole Schwen

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