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Genealogy and functional relationships among neuronal ion channel models in the NEURON language
William F Podlaski1 Alex Seeholzer2 Rajnish Ranjan3 Tim P Vogels1
1Centre for Neural Circuits and Behaviour, University of Oxford 2Laboratory of Computational Neuroscience, Ecole Polytechnique Federale de Lausanne 3Brain Mind Institute, Ecole Polytechnique Federale de Lausanne

NEURON is a widely used simulation environment for spatially extended multi-compartmental neuron models with diverse populations of ion channels. The online database ModelDB archives a multitude of published NEURON models, facilitating their reuse and allowing for expansion upon previously written code. The database includes thousands of individual ion channel models, which makes it increasingly difficult to understand the relations between different models, and to determine which pieces might be suitable for reuse in a new model. Here, we present an analysis of the over 2000 available ion channel models in ModelDB based on channel type and available reference information. We quantify the similarity in kinetics between models using a series of standardized voltage clamp simulation protocols and subsequent cluster analysis. Channel "family relations," i.e. citation links and duplications of channels, as well as similarity of kinetics between channel models, are combined into genealogical trees and dendrograms. All of the data is made available through a web interface as an aid for researchers in the biophysical modeling community. Additionally, we provide tools for uploading new channel models, as well as experimentally recorded current traces, allowing for immediate quantitative comparison with all models currently in the database.