neuroelectro.org a window to the world’s neurophysiology data shreejoy tripathy university of...
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NeuroElectro.orgA window to the world’s neurophysiology data
Shreejoy TripathyUniversity of British Columbia, Canada
Email: [email protected]: @neuronJoy
Main Idea• Given that there is an extensive neuron
electrophysiology literature, what can we learn by compiling it?
PubMed search: neuron AND (electrophysiology OR biophysical OR neurophysiology)
>45K articles
Electrophysiology literature is notoriously heterogeneous
Electrophysiology literature is notoriously heterogeneous
Input resistancemeasurement differences
NeuroElectro overall methodology
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Semi-automated text-mining overview
• Identify within data tables:– Neuron types (from
NeuroLex.org)– Biophysical properties (in
normotypic conditions)– Biophysical data values
• Experimental conditions defined within methods sections
• Text-mined data is then checked by experts
Tripathy et al, 2014
“Experiments were conducted in acutely prepared brain slices of 24- to 28-day-old (65–120 g) male Wistar rats.”
NeuroElectro.org web interface
Code at github.com/neuroelectroData at neuroelectro.org/api
Database statistics
• Currently 100 neuron types, >300 articles
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Resting membrane potential
mV
Extensive variability among NeuroElectro data
Netzebrand et al, 1999
Tripathy et al, in revision
Input resistance
MΩ
Accounting for differences in experimental conditions
• Explain variability in electrophysiological data through influence of experimental conditions:– species/strain – electrode type– animal age,– recording temperature– in vitro/in vivo/cell culture– junction potential
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Electrode type
Tripathy et al, in revision
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Neu
ron
clus
terin
g on
bas
is o
f el
ectr
ophy
siol
ogy
Tripathy et al, in revision
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Whole-genome correlation of gene expression and electro-diversity
20,000 genes
Patterns of gene expression
Electrophysiologicalphenotypes
Tripathy et al, in revision/in progress
Systematic variation among
neuron types
Making hypotheses on electrophysiology - gene expression relationships
• Explaining electrophysiological phenotypes in terms of underlying gene expression (and vice versa)
Future directions
• Continuing to expand NeuroElectro– More neuron types– More domains• Synaptic plasticity
• Continuing to demonstrate the value of data integration– How can we move to a situation where
experimentalists are willingly sharing their data?
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Acknowledgements• Pavlidis Lab @ UBC• Urban Lab @ CMU• Gerkin Lab @ ASU
Shreejoy TripathyEmail: [email protected]
Twitter: @neuronJoyURL: neuroelectro.org
Code: github.com/neuroelectro
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Mapping neuron electrophysiology to gene expression
Neuron typeresolution
Cell layerresolution
Neuron type to cell layer mapping is approximate. Will be improved in future iterations with high resolution data.
Neocortex L5/6pyramidal cell
Neocortex layer 5/6
Neocortex basket cell
Neocortex
20,000 genes
Finding genes most correlated with electrophysiological diversity
Assessing predictive power between gene expression and electrophysiology