Our database provides a comprehensive and quantitative assay of ion channel models currently available in the neuroscientific modeling community, all browsable in interactive visualizations.

Currently, the database contains 3487 models with 2378 quantitatively evaluated ion channels for the NEURON simulator.

Learn more »

The ICG Project is an initiative of the CNCB @ University of Oxford in collaboration with the LCN @ EPFL.

Channel Browser

A graphical user interface to all channels currently available in our database. We offer several interactive data views to best help you choose ion channel models.

Browse channels »


Together we can improve ICG! Upload your own channel models or submit tickets to correct existing ones should you find errors in our database.

Submit a channel » Create a ticket »


All our data is accessible via an API. This enables you to run automated evaluations against current traces, or simply evaluate the metadata.

View API description»

"An exemplary site that will accelerate the ability to flexibly and biophysically accurately model neurons across species, brain regions and developmental time-points."
"ICG is wonderful! It massively reduces the time and effort investments in my lab every time we need to model a new ion channel."
"Your database of ion channels organizes them in a way that is extraordinarily useful for modelers. It has long been a struggle to pick reasonable ion channel parameters for building detailed neuronal models. We expect to use ICG extensively to navigate the confused map of ion channels."
"The ion channel genealogy database and accompanying website constitutes a much needed resource for theoretical neuroscience. It will greatly assist us in creating morphologically detailed models in NEURON. As a tool it will not only save valuable time, but also provide fresh insight into the functional relationships between ion channels. Open access tools such as this are critical for the growth of fledgling computational neuroscience communities in developing world contexts such as South Africa."
"Constructing biophysical neuron models has been a time demanding and gruelling process for the past 30 years. ICGenealogy suddenly makes it easy, convenient and even fun. It provides just about all the tools you could wish for at your finger tips, at a level of UI sophistication and user-friendliness that is simply unprecedented in our field. In one word: awesome."
"I think it is important to federate data as you are doing, and this looks a very promising tool and a really useful database which will save a lot of time to modellers!"
"ICG is a great addition to the all too slowly growing ecosystem of neuroinformatics tools and databases. As we all know, more and more often the knowledge is available out there, somewhere, we just cannot find it. ICG provides a highly practical and beautiful interface to the available ion channel models characteristics with practical mechanisms for knowledge extension through user submissions. Of course, proper curation of incoming data, integration with other resources, and especially sustainability are critical for long-term ICG success but we shall definitely be using this resource shopping for new ion channel models. Very useful complement to Channelpedia."
"ICG is a great resource, not only that it speeds up the modelling of biophysically realistic neurons by making ion channel models readily available but also brings order to the zoo of ion channels."
"This is a huge amount of work and really a wonderful gift to anyone using ion channel models. We are very much looking forward to using this database soon for our future models."
"I am extremely excited about ICG - it is a great resource for the neuroscience modeling community and is a perfect example of how a commitment to open science can transform our approach to creating, using, and sharing models and what we can learn from them."
"This is a great new neuronal modelling resource - a really useful addition to ModelDB. It makes my the beginning of a new project so much more enjoyable. The fear of overlooking the ‘right’ model, or using the wrong one is gone! Good job - keep it up!"
"A great resource for conductance-based modeling."
"Such comprehensive catalog is a huge contribution to the whole community."
"ICGenealogy is a great resource for the computational neuroscience field. It was desperately needed. It has dramatically reduced the time I needed to collect ion channel model information from the literature, and as a result has helped me to do systematic comparisons of large numbers of channel types that would be otherwise difficult or impossible to achieve."
"ICG is an extremely helpful tool if you want to do proper modeling involving ion channels."
Paper available in preprint @ 2.7.2016

If you're looking for details in how the ICGenealogy framework works, you can now access our paper in preprint from Biorxiv:

William F Podlaski, Alexander Seeholzer, Lukas N Groschner, Gero Miesenboeck, Rajnish Ranjan, and Tim P Vogels. "ICGenealogy: Mapping the Function of Neuronal Ion Channels in Model and Experiment." bioRxiv, June 16, 2016. doi:10.1101/058685.

ICGenealogy 0.3.1 Update @ 6.5.2016

We're happy to annonce that we just rolled out a bunch of updates, improving on features generally and making our site more secure.

Major changes

  • Server: All communication is now encrypted over SSL
  • API: Improved caching
  • API: Updated structure of the API, including autogenerated documentation
  • Channel submission: enabled for Kv, Nav, Cav and IH classes.
  • Channel submission: improved logging for failed NEURON simulations. You now receive asyncronous messages on completion/failure of your channel simulations, including full error reports for debugging.

University of Oxford Centre for Neural Circuits and Behaviour Laboratory of Computational Neuroscience EPFL Lausanne