Below you will find pages that utilize the taxonomy term “pcsf”
Blog
Salmonella - Host Interaction Network - A Detailed, Better Visualization
We’re almost done with the analyses and we’re making the final visualization of the network. As I previously posted, the network was clustered and visualized by time points. After that, we have done several more analyses and here I report how we visualized them. I’m going to post more about how we did the analyses separately.
First, the nodes are grouped into experimental and not experimental (PCSF nodes). This can easily be done by parsing experimental network output and network outputs of PCSF.
Blog
Network Clustering with NeAT - RNSC Algorithm
As we have obtained proteins at different times points from the experimental data, then we have found intermediate nodes (from human interactome) using PCSF algorithm and finally with a special matrix from the network that PCSF created, we have validated the edges and also determined edge directions using an approach which a divide and conquer (ILP) approach for construction of large-scale signaling networks from PPI data. The resulting network is a directed network and will be used and visualized for further analyses.
Blog
Reconstructed Salmonella Signaling Network Visualized and Colored
After fold changes were obtained and HGNC names were found for each phosphopeptide, these were used to construct Salmonella signaling network using PCSF and then with the nodes that PCSF found as well, we generated a matrix which has node in the rows and time points in the columns and each cell shows the presence of corresponding protein under the corresponding time point(s).
The matrix has 658 nodes (proteins) and 4 time points as indicated before: 2 min, 5 min, 10 min and 20 min.