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Front Neuroinform. 2018 Jun 26;12:38. doi: 10.3389/fninf.2018.00038. eCollection 2018.

FindSim: A Framework for Integrating Neuronal Data and Signaling Models.

Author information

1
National Centre for Biological Sciences, Bangalore, India.
2
Tata Institute of Fundamental Research, The University of Trans-Disciplinary Health Sciences and Technology, Bangalore, India.
3
Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.
4
ZJU-UoE Institute, Zhejiang University, Hangzhou, China.

Abstract

Current experiments touch only small but overlapping parts of very complex subcellular signaling networks in neurons. Even with modern optical reporters and pharmacological manipulations, a given experiment can only monitor and control a very small subset of the diverse, multiscale processes of neuronal signaling. We have developed FindSim (Framework for Integrating Neuronal Data and SIgnaling Models) to anchor models to structured experimental datasets. FindSim is a framework for integrating many individual electrophysiological and biochemical experiments with large, multiscale models so as to systematically refine and validate the model. We use a structured format for encoding the conditions of many standard physiological and pharmacological experiments, specifying which parts of the model are involved, and comparing experiment outcomes with model output. A database of such experiments is run against successive generations of composite cellular models to iteratively improve the model against each experiment, while retaining global model validity. We suggest that this toolchain provides a principled and scalable way to tackle model complexity and diversity of data sources.

KEYWORDS:

LTP; biochemistry; pharmacology; signaling pathway; simulation; synaptic signaling; systems biology

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