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To check the significance of the above result, we observe the membership of the set of connector hubs in the corresponding randomized network (Fig. S3).
The larger set of connector proteins has been under investigation and would be analyzed in future work.
We used the Cytoscape plug-in ClueGO [ 33] to identify gene ontology (GO) terms (from level 3 to level 8 of the GO biological process hierarchy) that were significantly enriched with the complete set of connector proteins and the connector proteins of two diseases pairs ALS-PD and FTD-PD.
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Let M={e|e∈E and the endpoints are red and yellow } and C be the set of connectors.
In this section, we propose a novel algorithm to find a set of connectors C such that S1∪C forms a subtree.
We introduce a set of "connectors" to bridge models, both within and across the "upstream" activities in the software development lifecycle (specifically, requirements, architecture, and design).
We will use M⊆𝒳1×𝒳2 to denote a set of connectors between 𝒳1 and 𝒳2.
Furthermore, the set of connectors developed in the context of this work can also be adapted and reused in the integration of other tools and data sources in the domain.
This lemma is used to prove the following theorem: Let N1 and N2 be two rooted phylogenetic networks on 𝒳1 and 𝒳2, respectively and let M be a set of connectors between 𝒳1 and 𝒳2.
An optimal tanglegram can now be defined as follows: Let N1 and N2 be two rooted phylogenetic networks on 𝒳1 and 𝒳2, respectively, and let M be a set of connectors between 𝒳1 and 𝒳2.
We were able to successfully map all concepts representing a data item either consumed or produced by the developed set of connectors to a concept defined in the gene expression ontology.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com