FindSim: A Framework for Integrating Neuronal Data and Signaling Models

Viswan, Nisha A.; HarshaRani, Gubbi Vani; Stefan, Melanie I.; Bhalla, Upinder S.

doi:10.3389/fninf.2018.00038

Cited by 12 publications

(17 citation statements)

References 70 publications

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“…SBML, MATLAB ® SimBiology ® or MOD. Our workflow is modularized into different steps allowing the use of each step depending on the need and ensuring interoperability with other tools, such as those described in a similar endeavor named FindSim (Viswan et al 2018). There are distinct advantages to the workflow, by enforcing a common standard for information exchange, it inherently makes the models more generalizable and reduces the likelihood that simulation results are artifacts of a particular simulator, and nonetheless, it gives users the flexibility to leverage the strengths of each different simulation environment and provides distinct stages of processing that would not be possible in any single simulator.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, we made two other use cases available for testing other parts of the workflow, with more information in the supplement. More extensive testing was done with a model of the mitogen-activated protein kinase (MAPK) cascade provided by the FindSim workflow (Viswan et al 2018) and results can be found in the supplementary materials.…”

Section: Examples Of Software and Toolboxes Used In Systems Biologymentioning

confidence: 99%

“…The model has 102 species, 102 reactions and 160 parameters. We rebuilt the model in SBtab and reproduced simulations of the two test experiments from Viswan et al 2018 [Fig. 7B - C].…”

Section: Supplementary Materialsmentioning

confidence: 99%

“…The medium spiny neuron model (Lindroos et al 2018) used in NEURON simulations is available in ModelDB database (RRID:SCR_007271) with access code 237653. The FindSim use case model is available in https://github.com/BhallaLab/FindSim (Viswan et al 2018).…”

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confidence: 99%

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A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Santos

Pajo

Trpevski

et al. 2020

Preprint

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Neuroscience incorporates knowledge from a range of scales from molecular dynamics to neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a variety of different software tools in the model building and analysis process. Systems biology, for instance, is among the more standardized fields. However, conversion between different model formats and interoperability between various tools is still somewhat problematic. To offer our take on tackling these shortcomings and by keeping in mind the FAIR (findability, accessibility, interoperability, reusability) data principles, we have developed a workflow for building and analyzing biochemical pathway models using pre-existing tools that could be utilized for the storage and refinement of models in all phases of development. We have chosen the SBtab format which allows the storage of biochemical models and associated data in a single file and provides a human readable set of syntax rules. Next, we implement custom-made MATLAB® scripts to perform parameter estimation and sensitivity analysis used in model refinement. Additionally, we have developed a web-based application for biochemical models that allows simulations with either a network free solver or stochastic solvers and incorporating geometry. Finally, we illustrate convertibility and use of a biochemical model in a biophysically detailed single neuron model by running multiscale simulations in NEURON. By this we can simulate the same model in three principally different simulators, describing different aspects of the system, and with a smooth conversion between the different model formats.

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Section: Discussionmentioning

confidence: 99%

Section: Examples Of Software and Toolboxes Used In Systems Biologymentioning

confidence: 99%

“…The model has 102 species, 102 reactions and 160 parameters. We rebuilt the model in SBtab and reproduced simulations of the two test experiments from Viswan et al 2018 [Fig. 7B - C].…”

Section: Supplementary Materialsmentioning

confidence: 99%

mentioning

confidence: 99%

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A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Santos

Pajo

Trpevski

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…The FindSim platform [ 85 ] facilitates collaboration between modellers and experimentalists on a project investigating neuronal signalling in Autism Spectrum Disorders. FindSim makes use of SBML to describe the model, but found it challenging to integrate other standards, especially when it came to capturing experimental data and comparing model outcomes to experiments.…”

Section: Emerging Standardization Needs and Multicellular Modelingmentioning

confidence: 99%

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

Waltemath

Golebiewski

Blinov

et al. 2020

Journal of Integrative Bioinformatics

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AbstractThis 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.

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A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

et al. 2021

View full text Add to dashboard Cite

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a variety of different software tools in the model building and analysis process. Here we focus on the scale of biochemical pathways, which is one of the main objects of study in systems biology. While systems biology is among the more standardized fields, conversion between different model formats and interoperability between various tools is still somewhat problematic. To offer our take on tackling these shortcomings and by keeping in mind the FAIR (findability, accessibility, interoperability, reusability) data principles, we have developed a workflow for building and analyzing biochemical pathway models, using pre-existing tools that could be utilized for the storage and refinement of models in all phases of development. We have chosen the SBtab format which allows the storage of biochemical models and associated data in a single file and provides a human readable set of syntax rules. Next, we implemented custom-made MATLAB® scripts to perform parameter estimation and global sensitivity analysis used in model refinement. Additionally, we have developed a web-based application for biochemical models that allows simulations with either a network free solver or stochastic solvers and incorporating geometry. Finally, we illustrate convertibility and use of a biochemical model in a biophysically detailed single neuron model by running multiscale simulations in NEURON. Using this workflow, we can simulate the same model in three different simulators, with a smooth conversion between the different model formats, enhancing the characterization of different aspects of the model.

show abstract

FindSim: A Framework for Integrating Neuronal Data and Signaling Models

Cited by 12 publications

References 70 publications

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

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

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

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