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Munarko Y, Rampadarath A, Nickerson D. Building a search tool for compositely annotated entities using Transformer-based approach: Case study in Biosimulation Model Search Engine (BMSE). F1000Res 2023; 12:162. [PMID: 37842339 PMCID: PMC10570691 DOI: 10.12688/f1000research.128982.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/25/2023] [Indexed: 10/17/2023] Open
Abstract
The Transformer-based approaches to solving natural language processing (NLP) tasks such as BERT and GPT are gaining popularity due to their ability to achieve high performance. These approaches benefit from using enormous data sizes to create pre-trained models and the ability to understand the context of words in a sentence. Their use in the information retrieval domain is thought to increase effectiveness and efficiency. This paper demonstrates a BERT-based method (CASBERT) implementation to build a search tool over data annotated compositely using ontologies. The data was a collection of biosimulation models written using the CellML standard in the Physiome Model Repository (PMR). A biosimulation model structurally consists of basic entities of constants and variables that construct higher-level entities such as components, reactions, and the model. Finding these entities specific to their level is beneficial for various purposes regarding variable reuse, experiment setup, and model audit. Initially, we created embeddings representing compositely-annotated entities for constant and variable search (lowest level entity). Then, these low-level entity embeddings were vertically and efficiently combined to create higher-level entity embeddings to search components, models, images, and simulation setups. Our approach was general, so it can be used to create search tools with other data semantically annotated with ontologies - biosimulation models encoded in the SBML format, for example. Our tool is named Biosimulation Model Search Engine (BMSE).
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Affiliation(s)
- Yuda Munarko
- Auckland Bioengineering Institute, University of Auckland, Auckland, 1010, New Zealand
| | - Anand Rampadarath
- Auckland Bioengineering Institute, University of Auckland, Auckland, 1010, New Zealand
- The New Zealand Institute for Plant and Food Research Limited, Auckland, New Zealand
| | - David Nickerson
- Auckland Bioengineering Institute, University of Auckland, Auckland, 1010, New Zealand
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2
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Schölzel C, Blesius V, Ernst G, Dominik A. Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: a software engineering perspective. NPJ Syst Biol Appl 2021; 7:27. [PMID: 34083542 PMCID: PMC8175692 DOI: 10.1038/s41540-021-00182-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 04/19/2021] [Indexed: 02/06/2023] Open
Abstract
Reuse of mathematical models becomes increasingly important in systems biology as research moves toward large, multi-scale models composed of heterogeneous subcomponents. Currently, many models are not easily reusable due to inflexible or confusing code, inappropriate languages, or insufficient documentation. Best practice suggestions rarely cover such low-level design aspects. This gap could be filled by software engineering, which addresses those same issues for software reuse. We show that languages can facilitate reusability by being modular, human-readable, hybrid (i.e., supporting multiple formalisms), open, declarative, and by supporting the graphical representation of models. Modelers should not only use such a language, but be aware of the features that make it desirable and know how to apply them effectively. For this reason, we compare existing suitable languages in detail and demonstrate their benefits for a modular model of the human cardiac conduction system written in Modelica.
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Affiliation(s)
- Christopher Schölzel
- Technische Hochschule Mittelhessen - University of Applied Sciences, Giessen, Germany.
| | - Valeria Blesius
- Technische Hochschule Mittelhessen - University of Applied Sciences, Giessen, Germany
| | - Gernot Ernst
- Vestre Viken Hospital Trust, Kongsberg, Norway
- University of Oslo, Oslo, Norway
| | - Andreas Dominik
- Technische Hochschule Mittelhessen - University of Applied Sciences, Giessen, Germany
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3
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Guidry ME, Nickerson DP, Crampin EJ, Nash MP, Loiselle DS, Tran K. Insights From Computational Modeling Into the Contribution of Mechano-Calcium Feedback on the Cardiac End-Systolic Force-Length Relationship. Front Physiol 2020; 11:587. [PMID: 32547426 PMCID: PMC7273927 DOI: 10.3389/fphys.2020.00587] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 05/11/2020] [Indexed: 11/23/2022] Open
Abstract
In experimental studies on cardiac tissue, the end-systolic force-length relation (ESFLR) has been shown to depend on the mode of contraction: isometric or isotonic. The isometric ESFLR is derived from isometric contractions spanning a range of muscle lengths while the isotonic ESFLR is derived from shortening contractions across a range of afterloads. The ESFLR of isotonic contractions consistently lies below its isometric counterpart. Despite the passing of over a hundred years since the first insight by Otto Frank, the mechanism(s) underlying this protocol-dependent difference in the ESFLR remain incompletely explained. Here, we investigate the role of mechano-calcium feedback in accounting for the difference between these two ESFLRs. Previous studies have compared the dynamics of isotonic contractions to those of a single isometric contraction at a length that produces maximum force, without considering isometric contractions at shorter muscle lengths. We used a mathematical model of cardiac excitation-contraction to simulate isometric and force-length work-loop contractions (the latter being the 1D equivalent of the whole-heart pressure-volume loop), and compared Ca2+ transients produced under equivalent force conditions. We found that the duration of the simulated Ca2+ transient increases with decreasing sarcomere length for isometric contractions, and increases with decreasing afterload for work-loop contractions. At any given force, the Ca2+ transient for an isometric contraction is wider than that during a work-loop contraction. By driving simulated work-loops with wider Ca2+ transients generated from isometric contractions, we show that the duration of muscle shortening was prolonged, thereby shifting the work-loop ESFLR toward the isometric ESFLR. These observations are explained by an increase in the rate of binding of Ca2+ to troponin-C with increasing force. However, the leftward shift of the work-loop ESFLR does not superimpose on the isometric ESFLR, leading us to conclude that while mechano-calcium feedback does indeed contribute to the difference between the two ESFLRs, it does not completely account for it.
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Affiliation(s)
- Megan E Guidry
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - David P Nickerson
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Edmund J Crampin
- Systems Biology Laboratory, School of Mathematics and Statistics, The University of Melbourne, Melbourne, VIC, Australia.,ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, School of Chemical and Biomedical Engineering, The University of Melbourne, Melbourne, VIC, Australia
| | - Martyn P Nash
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.,Department of Engineering Science, The University of Auckland, Auckland, New Zealand
| | - Denis S Loiselle
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.,Department of Physiology, The University of Auckland, Auckland, New Zealand
| | - Kenneth Tran
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
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4
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Cooling MT, Nickerson DP, Nielsen PMF, Hunter PJ. Modular modelling with Physiome standards. J Physiol 2016; 594:6817-6831. [PMID: 27353233 PMCID: PMC5134412 DOI: 10.1113/jp272633] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 06/26/2016] [Indexed: 01/27/2023] Open
Abstract
KEY POINTS The complexity of computational models is increasing, supported by research in modelling tools and frameworks. But relatively little thought has gone into design principles for complex models. We propose a set of design principles for complex model construction with the Physiome standard modelling protocol CellML. By following the principles, models are generated that are extensible and are themselves suitable for reuse in larger models of increasing complexity. We illustrate these principles with examples including an architectural prototype linking, for the first time, electrophysiology, thermodynamically compliant metabolism, signal transduction, gene regulation and synthetic biology. The design principles complement other Physiome research projects, facilitating the application of virtual experiment protocols and model analysis techniques to assist the modelling community in creating libraries of composable, characterised and simulatable quantitative descriptions of physiology. ABSTRACT The ability to produce and customise complex computational models has great potential to have a positive impact on human health. As the field develops towards whole-cell models and linking such models in multi-scale frameworks to encompass tissue, organ, or organism levels, reuse of previous modelling efforts will become increasingly necessary. Any modelling group wishing to reuse existing computational models as modules for their own work faces many challenges in the context of construction, storage, retrieval, documentation and analysis of such modules. Physiome standards, frameworks and tools seek to address several of these challenges, especially for models expressed in the modular protocol CellML. Aside from providing a general ability to produce modules, there has been relatively little research work on architectural principles of CellML models that will enable reuse at larger scales. To complement and support the existing tools and frameworks, we develop a set of principles to address this consideration. The principles are illustrated with examples that couple electrophysiology, signalling, metabolism, gene regulation and synthetic biology, together forming an architectural prototype for whole-cell modelling (including human intervention) in CellML. Such models illustrate how testable units of quantitative biophysical simulation can be constructed. Finally, future relationships between modular models so constructed and Physiome frameworks and tools are discussed, with particular reference to how such frameworks and tools can in turn be extended to complement and gain more benefit from the results of applying the principles.
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Affiliation(s)
| | | | - Poul M. F. Nielsen
- Auckland Bioengineering Institutethe University of AucklandNew Zealand
- Department of Engineering Sciencethe University of AucklandNew Zealand
| | - Peter J. Hunter
- Auckland Bioengineering Institutethe University of AucklandNew Zealand
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5
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Nickerson D, Atalag K, de Bono B, Geiger J, Goble C, Hollmann S, Lonien J, Müller W, Regierer B, Stanford NJ, Golebiewski M, Hunter P. The Human Physiome: how standards, software and innovative service infrastructures are providing the building blocks to make it achievable. Interface Focus 2016; 6:20150103. [PMID: 27051515 PMCID: PMC4759754 DOI: 10.1098/rsfs.2015.0103] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
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.
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Affiliation(s)
- David Nickerson
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Koray Atalag
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
- National Institute for Health Innovation (NIHI), The University of Auckland, Auckland, New Zealand
| | - Bernard de Bono
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Jörg Geiger
- Interdisciplinary Bank of Biomaterials and Data, University Hospital Würzburg, Würzburg, Germany
| | - Carole Goble
- School of Computer Science, University of Manchester, Manchester, UK
| | - Susanne Hollmann
- Research Center Plant Genomics and Systems Biology, Universitat Potsdam, Potsdam, Germany
| | | | - Wolfgang Müller
- Heidelberg Institute for Theoretical Studies (HITS gGmbH), Heidelberg, Germany
| | | | | | - Martin Golebiewski
- Heidelberg Institute for Theoretical Studies (HITS gGmbH), Heidelberg, Germany
| | - Peter Hunter
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
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6
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Nickerson DP, Ladd D, Hussan JR, Safaei S, Suresh V, Hunter PJ, Bradley CP. Using CellML with OpenCMISS to Simulate Multi-Scale Physiology. Front Bioeng Biotechnol 2015; 2:79. [PMID: 25601911 PMCID: PMC4283644 DOI: 10.3389/fbioe.2014.00079] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2014] [Accepted: 12/11/2014] [Indexed: 11/13/2022] Open
Abstract
OpenCMISS is an open-source modeling environment aimed, in particular, at the solution of bioengineering problems. OpenCMISS consists of two main parts: a computational library (OpenCMISS-Iron) and a field manipulation and visualization library (OpenCMISS-Zinc). OpenCMISS is designed for the solution of coupled multi-scale, multi-physics problems in a general-purpose parallel environment. CellML is an XML format designed to encode biophysically based systems of ordinary differential equations and both linear and non-linear algebraic equations. A primary design goal of CellML is to allow mathematical models to be encoded in a modular and reusable format to aid reproducibility and interoperability of modeling studies. In OpenCMISS, we make use of CellML models to enable users to configure various aspects of their multi-scale physiological models. This avoids the need for users to be familiar with the OpenCMISS internal code in order to perform customized computational experiments. Examples of this are: cellular electrophysiology models embedded in tissue electrical propagation models; material constitutive relationships for mechanical growth and deformation simulations; time-varying boundary conditions for various problem domains; and fluid constitutive relationships and lumped-parameter models. In this paper, we provide implementation details describing how CellML models are integrated into multi-scale physiological models in OpenCMISS. The external interface OpenCMISS presents to users is also described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modeling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use of other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (graphical processing unit and field programmable gate array) generated from CellML models is also discussed.
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Affiliation(s)
- David P. Nickerson
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - David Ladd
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Jagir R. Hussan
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Soroush Safaei
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Vinod Suresh
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Peter J. Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
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7
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Bergmann FT, Adams R, Moodie S, Cooper J, Glont M, Golebiewski M, Hucka M, Laibe C, Miller AK, Nickerson DP, Olivier BG, Rodriguez N, Sauro HM, Scharm M, Soiland-Reyes S, Waltemath D, Yvon F, Le Novère N. COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project. BMC Bioinformatics 2014; 15:369. [PMID: 25494900 PMCID: PMC4272562 DOI: 10.1186/s12859-014-0369-z] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2014] [Accepted: 10/30/2014] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND With the ever increasing use of computational models in the biosciences, the need to share models and reproduce the results of published studies efficiently and easily is becoming more important. To this end, various standards have been proposed that can be used to describe models, simulations, data or other essential information in a consistent fashion. These constitute various separate components required to reproduce a given published scientific result. RESULTS We describe the Open Modeling EXchange format (OMEX). Together with the use of other standard formats from the Computational Modeling in Biology Network (COMBINE), OMEX is the basis of the COMBINE Archive, a single file that supports the exchange of all the information necessary for a modeling and simulation experiment in biology. An OMEX file is a ZIP container that includes a manifest file, listing the content of the archive, an optional metadata file adding information about the archive and its content, and the files describing the model. The content of a COMBINE Archive consists of files encoded in COMBINE standards whenever possible, but may include additional files defined by an Internet Media Type. Several tools that support the COMBINE Archive are available, either as independent libraries or embedded in modeling software. CONCLUSIONS The COMBINE Archive facilitates the reproduction of modeling and simulation experiments in biology by embedding all the relevant information in one file. Having all the information stored and exchanged at once also helps in building activity logs and audit trails. We anticipate that the COMBINE Archive will become a significant help for modellers, as the domain moves to larger, more complex experiments such as multi-scale models of organs, digital organisms, and bioengineering.
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Affiliation(s)
- Frank T Bergmann
- Modelling of Biological Processes, BioQUANT/COS, University of Heidelberg, INF 267, Heidelberg, 69120, Germany.
| | - Richard Adams
- ResearchSpace, 24 Fountainhall Road, Edinburgh, EH9 2LW, UK.
| | - Stuart Moodie
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
- Current affiliation: Eight Pillars Ltd, 19 Redford Walk, Edinburgh, EH13 0AG, UK.
| | - Jonathan Cooper
- Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK.
| | - Mihai Glont
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | | | - Michael Hucka
- Computing and Mathematical sciences, California Institute of Technology, Pasadena, CA, 91125, USA.
| | - Camille Laibe
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | - Andrew K Miller
- Auckland Bioengineering Institute, University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland, 1142, New Zealand.
| | - David P Nickerson
- Auckland Bioengineering Institute, University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland, 1142, New Zealand.
| | - Brett G Olivier
- Systems Bioinformatics, VU University Amsterdam, Amsterdam, 1081 HV, The Netherlands.
| | - Nicolas Rodriguez
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.
| | - Herbert M Sauro
- Department of Bioengineering, University of Washington, Seattle, 98195, WA, USA.
| | - Martin Scharm
- Systems Biology and Bioinformatics, University of Rostock, Ulmenstrasse 69, Rostock, 18057, Germany.
| | - Stian Soiland-Reyes
- School of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
| | - Dagmar Waltemath
- Systems Biology and Bioinformatics, University of Rostock, Ulmenstrasse 69, Rostock, 18057, Germany.
| | - Florent Yvon
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | - Nicolas Le Novère
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.
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8
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Cooper J, Vik JO, Waltemath D. A call for virtual experiments: accelerating the scientific process. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2014; 117:99-106. [PMID: 25433232 DOI: 10.1016/j.pbiomolbio.2014.10.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2014] [Accepted: 10/13/2014] [Indexed: 02/04/2023]
Abstract
Experimentation is fundamental to the scientific method, whether for exploration, description or explanation. We argue that promoting the reuse of virtual experiments (the in silico analogues of wet-lab or field experiments) would vastly improve the usefulness and relevance of computational models, encouraging critical scrutiny of models and serving as a common language between modellers and experimentalists. We review the benefits of reusable virtual experiments: in specifying, assaying, and comparing the behavioural repertoires of models; as prerequisites for reproducible research; to guide model reuse and composition; and for quality assurance in the translational application of models. A key step towards achieving this is that models and experimental protocols should be represented separately, but annotated so as to facilitate the linking of models to experiments and data. Lastly, we outline how the rigorous, streamlined confrontation between experimental datasets and candidate models would enable a "continuous integration" of biological knowledge, transforming our approach to systems biology.
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Affiliation(s)
- Jonathan Cooper
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, UK.
| | - Jon Olav Vik
- Department of Animal and Aquacultural Sciences, Centre for Integrative Genetics, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway.
| | - Dagmar Waltemath
- Department of Systems Biology and Bioinformatics, University of Rostock, D-18051 Rostock, Germany.
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9
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Helikar T, Kowal B, McClenathan S, Bruckner M, Rowley T, Madrahimov A, Wicks B, Shrestha M, Limbu K, Rogers JA. The Cell Collective: toward an open and collaborative approach to systems biology. BMC SYSTEMS BIOLOGY 2012; 6:96. [PMID: 22871178 PMCID: PMC3443426 DOI: 10.1186/1752-0509-6-96] [Citation(s) in RCA: 134] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2012] [Accepted: 07/16/2012] [Indexed: 03/04/2023]
Abstract
BACKGROUND Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. RESULTS The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. CONCLUSIONS The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction.
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Affiliation(s)
- Tomáš Helikar
- Department of Mathematics, University of Nebraska at Omaha, Omaha, NE, USA.
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10
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Clayton RH, Nash MP, Bradley CP, Panfilov AV, Paterson DJ, Taggart P. Experiment-model interaction for analysis of epicardial activation during human ventricular fibrillation with global myocardial ischaemia. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2011; 107:101-11. [PMID: 21741985 DOI: 10.1016/j.pbiomolbio.2011.06.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2011] [Accepted: 06/22/2011] [Indexed: 11/25/2022]
Abstract
We describe a combined experiment-modelling framework to investigate the effects of ischaemia on the organisation of ventricular fibrillation in the human heart. In a series of experimental studies epicardial activity was recorded from 10 patients undergoing routine cardiac surgery. Ventricular fibrillation was induced by burst pacing, and recording continued during 2.5 min of global cardiac ischaemia followed by 30 s of coronary reflow. Modelling used a 2D description of human ventricular tissue. Global cardiac ischaemia was simulated by (i) decreased intracellular ATP concentration and subsequent activation of an ATP sensitive K⁺ current, (ii) elevated extracellular K⁺ concentration, and (iii) acidosis resulting in reduced magnitude of the L-type Ca²⁺ current I(Ca,L). Simulated ischaemia acted to shorten action potential duration, reduce conduction velocity, increase effective refractory period, and flatten restitution. In the model, these effects resulted in slower re-entrant activity that was qualitatively consistent with our observations in the human heart. However, the flattening of restitution also resulted in the collapse of many re-entrant waves to several stable re-entrant waves, which was different to the overall trend we observed in the experimental data. These findings highlight a potential role for other factors, such as structural or functional heterogeneity in sustaining wavebreak during human ventricular fibrillation with global myocardial ischaemia.
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Affiliation(s)
- R H Clayton
- Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello S14DP, UK.
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11
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Nickerson DP, Terkildsen JR, Hamilton KL, Hunter PJ. A tool for multi-scale modelling of the renal nephron. Interface Focus 2011; 1:417-25. [PMID: 22670210 DOI: 10.1098/rsfs.2010.0032] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2010] [Accepted: 03/07/2011] [Indexed: 11/12/2022] Open
Abstract
We present the development of a tool, which provides users with the ability to visualize and interact with a comprehensive description of a multi-scale model of the renal nephron. A one-dimensional anatomical model of the nephron has been created and is used for visualization and modelling of tubule transport in various nephron anatomical segments. Mathematical models of nephron segments are embedded in the one-dimensional model. At the cellular level, these segment models use models encoded in CellML to describe cellular and subcellular transport kinetics. A web-based presentation environment has been developed that allows the user to visualize and navigate through the multi-scale nephron model, including simulation results, at the different spatial scales encompassed by the model description. The Zinc extension to Firefox is used to provide an interactive three-dimensional view of the tubule model and the native Firefox rendering of scalable vector graphics is used to present schematic diagrams for cellular and subcellular scale models. The model viewer is embedded in a web page that dynamically presents content based on user input. For example, when viewing the whole nephron model, the user might be presented with information on the various embedded segment models as they select them in the three-dimensional model view. Alternatively, the user chooses to focus the model viewer on a cellular model located in a particular nephron segment in order to view the various membrane transport proteins. Selecting a specific protein may then present the user with a description of the mathematical model governing the behaviour of that protein-including the mathematical model itself and various simulation experiments used to validate the model against the literature.
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Affiliation(s)
- David P Nickerson
- Auckland Bioengineering Institute , The University of Auckland , Auckland , New Zealand
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12
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Miller AK, Yu T, Britten R, Cooling MT, Lawson J, Cowan D, Garny A, Halstead MDB, Hunter PJ, Nickerson DP, Nunns G, Wimalaratne SM, Nielsen PMF. Revision history aware repositories of computational models of biological systems. BMC Bioinformatics 2011; 12:22. [PMID: 21235804 PMCID: PMC3033326 DOI: 10.1186/1471-2105-12-22] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2010] [Accepted: 01/14/2011] [Indexed: 11/10/2022] Open
Abstract
Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model Repository software to be fully revision history aware, by building it on top of Mercurial, an existing DVCS. We have demonstrated the utility of this approach, when used in conjunction with the model composition facilities in CellML, to build and understand more complex models. We have also demonstrated the ability of the repository software to present version history to casual users over the web, and to highlight specific versions which are likely to be useful to users. Conclusions Providing facilities for maintaining and using revision history information is an important part of building a useful repository of computational models, as this information is useful both for understanding the source of and justification for parts of a model, and to facilitate automated processes such as merges. The availability of fully revision history aware repositories, and associated tools, will therefore be of significant benefit to the community.
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Affiliation(s)
- Andrew K Miller
- Auckland Bioengineering Institute, The University of Auckland, Private Bag 92019, Auckland, NZ.
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Miller AK, Marsh J, Reeve A, Garny A, Britten R, Halstead M, Cooper J, Nickerson DP, Nielsen PF. An overview of the CellML API and its implementation. BMC Bioinformatics 2010; 11:178. [PMID: 20377909 PMCID: PMC2858041 DOI: 10.1186/1471-2105-11-178] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2009] [Accepted: 04/08/2010] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND CellML is an XML based language for representing mathematical models, in a machine-independent form which is suitable for their exchange between different authors, and for archival in a model repository. Allowing for the exchange and archival of models in a computer readable form is a key strategic goal in bioinformatics, because of the associated improvements in scientific record accuracy, the faster iterative process of scientific development, and the ability to combine models into large integrative models.However, for CellML models to be useful, tools which can process them correctly are needed. Due to some of the more complex features present in CellML models, such as imports, developing code ab initio to correctly process models can be an onerous task. For this reason, there is a clear and pressing need for an application programming interface (API), and a good implementation of that API, upon which tools can base their support for CellML. RESULTS We developed an API which allows the information in CellML models to be retrieved and/or modified. We also developed a series of optional extension APIs, for tasks such as simplifying the handling of connections between variables, dealing with physical units, validating models, and translating models into different procedural languages.We have also provided a Free/Open Source implementation of this application programming interface, optimised to achieve good performance. CONCLUSIONS Tools have been developed using the API which are mature enough for widespread use. The API has the potential to accelerate the development of additional tools capable of processing CellML, and ultimately lead to an increased level of sharing of mathematical model descriptions.
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Affiliation(s)
- Andrew K Miller
- Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
| | - Justin Marsh
- Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
| | - Adam Reeve
- Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
| | - Alan Garny
- Department of Physiology, Anatomy and Genetics, Sherrington Building, Parks Road, Oxford OX1 3PT, UK
| | - Randall Britten
- Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
| | - Matt Halstead
- Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
| | - Jonathan Cooper
- Oxford University Computing Laboratory, Wolfson Building, Parks Road, Oxford OX1 3QD, UK
| | - David P Nickerson
- Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
| | - Poul F Nielsen
- Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
- Department of Engineering Science, The University of Auckland, Auckland, NZ
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Nickerson DP, Buist ML. A physiome standards-based model publication paradigm. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2009; 367:1823-44. [PMID: 19380314 DOI: 10.1098/rsta.2008.0296] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
In this era of widespread broadband Internet penetration and powerful Web browsers on most desktops, a shift in the publication paradigm for physiome-style models is envisaged. No longer will model authors simply submit an essentially textural description of the development and behaviour of their model. Rather, they will submit a complete working implementation of the model encoded and annotated according to the various standards adopted by the physiome project, accompanied by a traditional human-readable summary of the key scientific goals and outcomes of the work. While the final published, peer-reviewed article will look little different to the reader, in this new paradigm, both reviewers and readers will be able to interact with, use and extend the models in ways that are not currently possible. Here, we review recent developments that are laying the foundations for this new model publication paradigm. Initial developments have focused on the publication of mathematical models of cellular electrophysiology, using technology based on a CellML- or Systems Biology Markup Language (SBML)-encoded implementation of the mathematical models. Here, we review the current state of the art and what needs to be done before such a model publication becomes commonplace.
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Affiliation(s)
- David P Nickerson
- Division of Bioengineering, National University of Singapore, Singapore 117574, Republic of Singapore
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Beard DA, Britten R, Cooling MT, Garny A, Halstead MD, Hunter PJ, Lawson J, Lloyd CM, Marsh J, Miller A, Nickerson DP, Nielsen PM, Nomura T, Subramanium S, Wimalaratne SM, Yu T. CellML metadata standards, associated tools and repositories. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2009; 367:1845-67. [PMID: 19380315 PMCID: PMC3268215 DOI: 10.1098/rsta.2008.0310] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The development of standards for encoding mathematical models is an important component of model building and model sharing among scientists interested in understanding multi-scale physiological processes. CellML provides such a standard, particularly for models based on biophysical mechanisms, and a substantial number of models are now available in the CellML Model Repository. However, there is an urgent need to extend the current CellML metadata standard to provide biological and biophysical annotation of the models in order to facilitate model sharing, automated model reduction and connection to biological databases. This paper gives a broad overview of a number of new developments on CellML metadata and provides links to further methodological details available from the CellML website.
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Affiliation(s)
- Daniel A. Beard
- Department of Physiology, Medical College of WisconsinMilwaukee, WI 53226, USA
| | - Randall Britten
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
| | - Mike T. Cooling
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
| | - Alan Garny
- Department of Physiology, Anatomy and Genetics, University of OxfordOxford OX1 2JD, UK
| | - Matt D.B. Halstead
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
| | - Peter J. Hunter
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
- Department of Physiology, Anatomy and Genetics, University of OxfordOxford OX1 2JD, UK
| | - James Lawson
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
| | - Catherine M. Lloyd
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
| | - Justin Marsh
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
| | - Andrew Miller
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
| | - David P. Nickerson
- Division of Bioengineering, National University of SingaporeSingapore 117574, Republic of Singapore
| | - Poul M.F. Nielsen
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
- Author for correspondence ()
| | - Taishin Nomura
- Department of Mechanical Science and Bioengineering, Osaka UniversitySuita, Osaka 565-0871, Japan
| | - Shankar Subramanium
- Department of Bioengineering, University of California, San DiegoLa Jolla, CA 92093, USA
| | | | - Tommy Yu
- Auckland Bioengineering Institute, University of AucklandAuckland 1142, New Zealand
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