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The first connectivity measure is intramodular connectivity defined as (4) where n(q ) is the number of genes in the q th module.
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Finally, the third connectivity profile was characterized by increased coupling of the three control networks (frontoparietal, salience, cingulo-opercular) with one another and with the remaining systems, particularly the subcortical and the two networks showing declining segregation with age.
The second connectivity measure is the module eigengene based connectivity, (also known as the signed module membership measure [ 33]), defined as (5) where E(q ) is the eigengene of the q th module (see equations 9 and 10 in the Methods section) and x i is the expression profile of the gene i.
In the first case, connectivity measures are evaluated on the time series recorded by MEG/EEG sensors.
The first order connectivity that each viral protein has with the host proteins can be extracted directly from the data.
The resulting connectivity matrix was compared with both the ABA neuronal tracer-based connectivity matrix and to the first tractography-based connectivity matrix using the methods described in the previous section.
The second structural connectivity measurement was made by analyzing the seed plane created between the pairs of ROIs.
In the second case, connectivity measures are evaluated on time series that represent the activity of individual brain areas.
Because there is little prior evidence available on the likely spatial associations among subjects, the first-order connectivity matrix based on nearest neighbor proximity is used.
2. RNA metabolism and transcriptional regulation The predicted pathogenesis-related functional orthologs with the second largest connectivity (98) is a putative DEAD/DEAH box ATP-dependent RNA helicase (PF3D7_1241800).
The first is modular connectivity, where the network consists of several modules that are fully connected inside and have no connections between them.
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