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Estimated peaks were added to complete clusters.
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We consider two approaches to complete-cluster inference that relate to methods proposed for observed-cluster inference.
The process of detecting complexes in our proposed algorithm consists of the following steps: 1. Calculating pair-wise similarities between bait proteins; 2. Clustering bait proteins to obtain preliminary seed clusters; 3. Expanding process to form complete clusters; 4. Filtering clusters and outputting final set of clusters.
In our study, measurement clusters with SAIF took significantly longer to complete than clusters without.
The pSZ77 tonB exbB exbD genes associated with cobN do not correspond to a complete cluster on the SZ chromosome, suggesting that transport of cobalamin and/or other organometallic complexes made the plasmid essential under the cultivation conditions used.
The same interpretation problem applies here: this association refers to the hypothetical "complete" clusters.
The clustering algorithm was set to complete linkage clustering using an uncentered correlation.
The clustering algorithm was set to complete linkage clustering using the uncentered Pearson correlation.
Finally, according to these clustering centers, a time scan clustering is designed for the rest of the points by density to complete the clustering.
Thirdly, a fine-tuning step is designed to complete the clustering task by assigning the unclustered links of the network to proper clusters while keeping the connectivity.
This example shows a model that ostensibly describes observed clusters but some of whose parameters relate only to a population of complete clusters with no obvious meaning.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com