An information management system is needed in order to:
- Integrate data related to ion channels in C. elegans from different sources
- Structure data for better representation
- Ease access to the data through scripts/APIs
- Keep data up-to-date
- Description about the ion channel
- Genetics, gene ontology, sequences, and locations
- Proteins, structures, and homology information
- Expression information and patterns in neurons/cells
- Phenotypes and functionalities
- Interaction network
- Channelopathies (ion channel diseases), known mutations, and pharmacological studies
- Available models and simulations
- Model type (from patch clamp studies, or estimation from known homologs)
- Experimental conditions (cell type, temperature, Reversal potential, age of the organism, etc.)
- Channel Properties (conductance, activation/inactivation parameters, etc.)
- Cell and synapse properties (membrane capacitance, surface area, external ion concentration, etc.)
- Graphs demonstrating kinetics
- Representation files for each model/simulation (NeuroML and LEMS respectively)
- Evidence(s) for all the assertions
Biological information about each ion channel was obtained from the WormBase database which is available in this spread sheet file. Every tuple in the spread sheet has some links to its WormBase entry that could be used for more information.
In the ion channels with properties sheet, you can find properties, such as type, subtype, kinetic properties, etc. for every ion channel.
The references column in this table contains links which reference publications on Mendeley.
To keep data in a structured and easy-to-access format, we use the PyOpenWorm, from the OpenWorm project. The database stores data for generating model files along with annotations describing the origins of the data. PyOpenWorm utilizes RDF which facilitates integration of data from disparate sources. For example, it is possible to ask PyOpenWorm to list all the ion channels of a muscle cell named MDL08, with evidence:
muscle = PyOpenWorm.Muscle('MDL08') muscle.channels() ['EGL-19', 'SHK-1', 'SHL-1'] #look up what reference says this muscle has an ion channel EGL-19 muscle.get_reference(0,'EGL-19') ['http://dx.doi.org/10.1083%2Fjcb.200203055']
PyOpenWorm allows easy access to data about ion channels, either for human or machine reading.
For full usage of the PyOpenWorm API, take a look at this document
Final models are represented in NeuroML2 format which is an XML based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models. You can find an example for this representation here. Single channel kinetics are described by a NeuroML file, which could then be integrated with other channels and properties in a LEMS format for final simulations (LEMS sample file). For more information see this tutorial.
In addition to jNeuroML, these representation files could be used in different tools that support neuronal simulation. Here you can find an example for a simulation of muscle cell ion channels in C. elegans.
In order to get informed about new publications about ion channels in C. elegans and also any update on existing data, an update management system should be implemented.
You can find open/closed issues for this topic here