Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network.
Bánk G. FenyvesGábor S. SzilágyiZsolt VassyCsaba SotiPeter CsermelyPublished in: PLoS Comput. Biol. (2020)
Keyphrases
- gene expression data
- gene expression
- microarray
- spiking neural networks
- gene networks
- learning rules
- caenorhabditis elegans
- microarray data
- prediction accuracy
- cancer classification
- gene selection
- data sets
- high dimensionality
- feature selection
- single neuron
- gene expression datasets
- gene expression analysis
- network structure
- synaptic plasticity
- gene expression profiles
- gene expression profiling
- protein interaction
- gene regulatory networks
- microarray datasets
- dna microarray
- synaptic weights
- spiking neurons
- input patterns
- analysis of gene expression data
- gene expression patterns
- gene expression data analysis
- gene expression data sets
- microarray gene expression data
- action potentials
- high dimensional data
- biologically inspired
- spike trains
- sensory inputs
- regulatory networks
- complex networks
- network model