In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 16, No. 12 ( 2020-12-21), p. e1007974-
Abstract:
Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C . elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool ( http://EleganSign.linkgroup.hu ) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1007974
DOI:
10.1371/journal.pcbi.1007974.g001
DOI:
10.1371/journal.pcbi.1007974.g002
DOI:
10.1371/journal.pcbi.1007974.g003
DOI:
10.1371/journal.pcbi.1007974.g004
DOI:
10.1371/journal.pcbi.1007974.g005
DOI:
10.1371/journal.pcbi.1007974.t001
DOI:
10.1371/journal.pcbi.1007974.t002
DOI:
10.1371/journal.pcbi.1007974.s001
DOI:
10.1371/journal.pcbi.1007974.s002
DOI:
10.1371/journal.pcbi.1007974.s003
DOI:
10.1371/journal.pcbi.1007974.s004
DOI:
10.1371/journal.pcbi.1007974.s005
DOI:
10.1371/journal.pcbi.1007974.s006
DOI:
10.1371/journal.pcbi.1007974.s007
DOI:
10.1371/journal.pcbi.1007974.s008
DOI:
10.1371/journal.pcbi.1007974.s009
DOI:
10.1371/journal.pcbi.1007974.s010
DOI:
10.1371/journal.pcbi.1007974.s011
DOI:
10.1371/journal.pcbi.1007974.s012
DOI:
10.1371/journal.pcbi.1007974.s013
DOI:
10.1371/journal.pcbi.1007974.s014
DOI:
10.1371/journal.pcbi.1007974.s015
DOI:
10.1371/journal.pcbi.1007974.s016
DOI:
10.1371/journal.pcbi.1007974.s017
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2020
detail.hit.zdb_id:
2193340-6
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