Display Settings:

Items per page
We are sorry, but NCBI web applications do not support your browser and may not function properly. More information

Results: 10

1.
Figure 9

Figure 9. From: A human functional protein interaction network and its application to cancer data analysis.

Front page of the web application for predicted functional interactions.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
2.
Figure 10

Figure 10. From: A human functional protein interaction network and its application to cancer data analysis.

Views of predicted functional interactions. (a) FIs in a reaction diagram. (b) FIs in a pathway diagram.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
3.
Figure 1

Figure 1. From: A human functional protein interaction network and its application to cancer data analysis.

Overview of procedures used to construct the functional interaction network. See text for details. BP, biological process.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
4.
Figure 8

Figure 8. From: A human functional protein interaction network and its application to cancer data analysis.

Subnetworks with pathways annotated for GBM clusters. Many pathways are hit by GBM candidate genes. Only four of them are labeled for two GBM clusters in this diagram to simplify the diagram. Colors and symbols are as in Figure 6.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
5.
Figure 6

Figure 6. From: A human functional protein interaction network and its application to cancer data analysis.

Plots of altered genes versus samples. The horizontal axis is the sample numbers, and the left vertical axis is the percentage of altered genes occurring in samples related to total altered genes. The right vertical axis is the average shortest path among altered genes occurring in samples. (a) The TCGA data set. (b) The Parsons data set.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
6.
Figure 7

Figure 7. From: A human functional protein interaction network and its application to cancer data analysis.

Subnetworks for GBM clusters. (a) The TCGA cluster. (b) The Parsons cluster. Shared GBM candidate genes are shown in yellow, non-shared candidate genes in aqua, and linker genes used to connect cancer genes in red. The node size is proportional to the number of samples bearing displayed altered genes. Other colors and symbols are as in Figure 2.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
7.
Figure 4

Figure 4. From: A human functional protein interaction network and its application to cancer data analysis.

Edge-betweenness network clustering results for the altered genes from the TCGA data set. Gene nodes in different clusters are displayed in different colors. GO cellular component annotation for clusters 0 and 1 are labeled in the diagram to show the major cellular localizations for genes in these two clusters. The node size is proportional to the number of samples bearing displayed altered genes.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
8.
Figure 5

Figure 5. From: A human functional protein interaction network and its application to cancer data analysis.

Hierarchical clustering of GBM samples in the TCGA data set based on altered gene occurrences in the network modules identified by the edge-betweenness algorithm. The rows are samples, while the columns are 17 network modules. In the central heat map, red rectangles represent samples having altered genes in modules, while green rectangles represent samples having no altered genes in modules. The vertical blue dashed line shows the cutoff value we used to select sample clusters from the hierarchical clustering. The right-most column lists sample types: green for primary GBM samples ('No' in Table S1B in [14]), blue for recurrent ones ('Rec' in Table S1B in [14]), and red for secondary ones ('Sec' in Table S1B in [14]).

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
9.
Figure 2

Figure 2. From: A human functional protein interaction network and its application to cancer data analysis.

Receiver operating characteristic curve for NBC trained with protein pairs extracted from Reactome pathways as the positive data set, and random pairs as the negative data set. This curve was created using an independent test data set generated from pathways imported from non-Reactome pathway databases. The positions for the cutoff values 0.25, 0.50 and 0.75 are marked from right to left in the inset. The area under the curve (AUC) for this receiver operating characteristic (ROC) curve is 0.93.

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.
10.
Figure 3

Figure 3. From: A human functional protein interaction network and its application to cancer data analysis.

Overlay of predicted functional interactions onto a human curated GBM pathway from the TCGA data set. Many genes can interact with multiple pathway genes. In this diagram, only genes interacting with one pathway gene are shown to minimize diagram clutter. Newly added genes are colored in light blue, while original genes are colored in grey. Newly added FIs are in blue, while original interactions are in other colors. FIs extracted from pathways are shown as solid lines (for example, PHLPP-AKT1), while those predicted based on NBC are shown as dashed lines (for example, KLF6-TP53). Extracted FIs involved in activation, expression regulation, or catalysis are shown with an arrowhead on the end of the line, while FIs involved in inhibition are shown with a 'T' bar. The original GBM pathway map in the Cytoscape format was downloaded from [69].

Guanming Wu, et al. Genome Biol. 2010;11(5):R53-R53.

Display Settings:

Items per page

Supplemental Content

Recent activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...
Write to the Help Desk