Results: 3

1.
Fig. 1.

Fig. 1. From: Improving the quality of protein similarity network clustering algorithms using the network edge weight distribution.

Clustering performance and edge weight distributions. Each plot shows the F-measure clustering performance metric for both the Force and MCL clustering algorithms over a range of binned −log(E-value) thresholds, together with a normalized edge weight distribution. (A) Amidohydrolase; edge weight distribution is rapid-descent. (B) SLC; edge weight distribution is rapid-descent. (C) Enolase; edge weight distribution is gradual-descent. (D) Kinase; edge weight distribution is gradual-descent.

Leonard Apeltsin, et al. Bioinformatics. 2011 February 1;27(3):326-333.
2.
Fig. 2.

Fig. 2. From: Improving the quality of protein similarity network clustering algorithms using the network edge weight distribution.

Visualizing MCL Clusters for the SLC Superfamily. Each set of clustering results has been visualized in Cytoscape using the Force-directed layout algorithm. Each node represents a protein, colored by the currently best available family assignments. Edges between nodes that are not in the same cluster have been removed from the similarity network prior to visualization. The unthresholded clustering results are shown in (A) and the thresholded clustering results are shown in (B). The same thresholded network is shown unclustered in Supplementary Figure 4b. The mapping of node colors to family assignments is shown in Supplementary Figure 5a.

Leonard Apeltsin, et al. Bioinformatics. 2011 February 1;27(3):326-333.
3.
Fig. 3.

Fig. 3. From: Improving the quality of protein similarity network clustering algorithms using the network edge weight distribution.

Visualizing MCL Clusters for the Kinase Superfamily. Each set of clustering results has been visualized in Cytoscape using the Force-directed layout algorithm. Each node represents a protein, colored by the currently best available family assignments. Edges between nodes that are not in the same cluster have been removed from the similarity network prior to visualization. The unthresholded clustering results are shown in (A) and the thresholded clustering results are shown in (B). The same thresholded network is shown as unclustered in Supplementary Figure 4d. The mapping of node colors to family assignments is shown in Supplementary Figure 5b.

Leonard Apeltsin, et al. Bioinformatics. 2011 February 1;27(3):326-333.

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