Abstract
The human synaptic proteome is a complex structure composed of over 5000 interacting proteins. Disruptions of these proteins have been associated with over 100 brain disorders making them of considerable interest to researchers examining the molecular antecedents of these disorders. The structure of the human synaptic proteome can be modelled as a network with each protein a vertex and each interaction an edge. A property of complex networks is community structure. Vertices form tightly interconnected groups (communities) with sparser connections between communities.
Previous studies have shown associations between communities detected in a subset of the synaptic proteome and cellular functions. The community detection methods used previously perform poorly at the scale of the complete synaptic proteome. We use a recently developed algorithm that scales well with increasing network size, to detect communities in a curated database of synaptic protein interactions. We test whether the communities have an enriched association with educational attainment using Gene Set Analysis.
Previous studies have shown associations between communities detected in a subset of the synaptic proteome and cellular functions. The community detection methods used previously perform poorly at the scale of the complete synaptic proteome. We use a recently developed algorithm that scales well with increasing network size, to detect communities in a curated database of synaptic protein interactions. We test whether the communities have an enriched association with educational attainment using Gene Set Analysis.
Original language | English |
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Publication status | Published - 22 Mar 2017 |
Event | Edinburgh Neuroscience Day 2017 - Edinburgh, United Kingdom Duration: 22 Mar 2017 → … |
Conference
Conference | Edinburgh Neuroscience Day 2017 |
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Country/Territory | United Kingdom |
City | Edinburgh |
Period | 22/03/17 → … |