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Expression-based gene network was built to define clusters of highly correlated sets of genes, called modules.
Commuting zones are constructed using, journey-to-work data and define clusters of counties with strong commuting ties.
This method is an agglomerative clustering building a hierarchy according to dissimilarities between objects, this hierarchy could then be thresholded to define clusters.
This should initially be easier for single-gene Mendelian childhood diseases, but emerging network approaches that define clusters of genes that drive a disease (such as diabetes, cancer, and Alzheimer's disease) could eventually be amenable to this strategy.
Coming from a business strategy approach (Porter 1998) to understand the determinants of competition, Porter and Ketels (2009) define clusters as "geographic agglomerations of companies, suppliers and service providers, and associated institutions in a particular field, linked by externalities and complementarities of various type" (2009 172).
The threshold p≤0.001 was used to define clusters, and only clusters with a minimum of 100 points were reported.
Finally the sequences on closely related branches of the tree are compared to define clusters with >90% of sequence identity.
Cluster analysis[18] was used to define clusters of co-coordinately changed genes after which the data was visualized using Treeview.
By cutting a phylogenetic tree at some level(s), it is possible to induce a partition of the taxa and define clusters, identifying thus non-overlapping groups of taxa or transmission events.
An 80% genetic relatedness cutoff was used to define clusters.
The component distributions of mixture model define clusters.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com