A Practical Guide to Cancer Systems Biology
Phosphorylation Data Analysis 77 Figure 1. An example layout of quantitative phosphosite data for use in DynaPho. software and ...
78 A Practical Guide to Cancer Systems Biology Figure 2. Submit data to DynaPho. The interface for (a) data selection and (b) da ...
Phosphorylation Data Analysis 79 Figure 3. Data exploration of quantitative phosphosite data. DynapPho provides several ways f ...
80 A Practical Guide to Cancer Systems Biology Figure 4. The submission page of “profile clustering” analysis. many missing valu ...
Phosphorylation Data Analysis 81 Figure 5. The result page of “profile clustering” showing clustered profiles and further func ...
82 A Practical Guide to Cancer Systems Biology Construction of function profile Gene set overrepresentation analysis is commonly ...
Phosphorylation Data Analysis 83 Figure 6. Visualization of overlap between enriched GO terms. Specify a query condition. By ...
84 A Practical Guide to Cancer Systems Biology Figure 7. Visualization of function profile in DynaPho. The color of the cell ind ...
Phosphorylation Data Analysis 85 Figure 8. Interaction networks. DynaPho provides two kinds of network view: (a) showing prote ...
86 A Practical Guide to Cancer Systems Biology Figure 9. Dynamic view of interaction networks. An example shows d ifferent condi ...
Phosphorylation Data Analysis 87 Figure 10. Visualization of kinase activity profile. The color of the cell indicates level of ...
88 A Practical Guide to Cancer Systems Biology Figure 11. Visualization of kinase/phosphatase–phosphosite association network. p ...
Phosphorylation Data Analysis 89 differential analyses provide different information to assist users to easily interpret their ...
8. Pathway and Network Analysis Chen-Tsung Huang and Hsueh-Fen Juan∗ Graduate Institute of Biomedical Electronics and Bioinforma ...
92 A Practical Guide to Cancer Systems Biology Installation of relevant R packages Several R packages have been made available ...
Pathway and Network Analysis 93 element names: exprs protocolData: none phenoData sampleNames: 01005 01010 ... LAL4 (128 total ...
94 A Practical Guide to Cancer Systems Biology sb<- as.character(sapply(sb, “[”)) names(sb)<-ez Note that any time if yo ...
Pathway and Network Analysis 95 Sample selection At this stage, you are getting interested in the tumor biology of acute lymph ...
96 A Practical Guide to Cancer Systems Biology samrData<-list(x=mergedData, y=classLabel, genenames=rownames(mergedData), l ...
Pathway and Network Analysis 97 Figure 1. QQ plot for SAM analysis. Red points represent DE upregulated genes (when class labe ...
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