Helpfile for the software

The following are explanations of various components that are not self-explanatory.

File menu:

• Read: reads an input file from your local directory. See the sample format for details. After reading, builds a network for single causal inferences (i.e., edges) only.
• Write: writes the current result to a file in your local directory. See the sample format for details.
• Exit: exits the program

Action menu:

• Clear: clears (deletes) the current network from consideration.
• Enzymatic edges: adds edges corresponding to the regulation of enzymes included as sources of edges marked enzymatic in the network. See sample format and the JCB paper for more details.
• Redundant edges: finds out and removes if there are duplicates edges in your file or the current result.
• Add pseudonodes: adds the double causal (i.e., three-vertex) inferences in the input file to the network via introducing pseudo-nodes if necessary.
• Collapse pseudonodes: collapses pseudo-nodes. The so-called PVC problem in the JCB paper.
• Reduction (slower): performs binary transitive reduction on the current network and also performs network sparsification based on the enzymatic edges of the network. Recommended for smaller networks, say no more than 150 nodes.
• Reduction (faster): performs binary transitive reduction on the current network and also performs network sparsification based on the enzymatic edges of the network. Recommended for larger networks, say more than 150 nodes.
• Collapse degree-2 pseudonodes: collapses pseudo-nodes that are of degree 2.
• Randomize before reduction: the transitive reduction step has steps where ties are broken arbitrarily. If you turn on this action, then such tie-breaking steps will be randomized, thus potentially giving different solutions at different runs of the transitive reduction. This option may be useful if you wanted to check out more than one solution for the transitive reduction step. Do not turn on this option if you want the same solution on the same input.

View menu:

• Info: shows basic information about the current graph (# of vertices, edges, connected components (undirected sense) and strongly connected components)
• Edge handle: displays the edges more visibly (and, hopefully more nicely).
• Show critical: shows critical edges with a different color.
• Show enzymatic: shows enzymatic edges with a different color.

Other functions:

• You can right click on a vertex on the canvas to change the name of that node. This may be especially useful in changing a real node to a pseudo-node or vice versa since the program assumes that nodes whose names start with an asterisk (*) are pseudo-nodes.
• You can right click on the edge handle to change the nature of an edge (e.g., from excitory to inhibitory or vice versa).

Refer to our papers

• Réka Albert, Bhaskar DasGupta and Eduardo Sontag, Inference of signal transduction networks from double causal evidence , Methods in Molecular Biology: Topics in Computational Biology, D. Fenyo (ed.), 673, Chapter 16, © Springer Science+Business Media, LLC, 2010.
• Sema Kachalo, Ranran Zhang, Eduardo Sontag, Réka Albert and Bhaskar DasGupta, NET-SYNTHESIS: A software for synthesis, inference and simplification of signal transduction networks , Bioinformatics, 24 (2), 293-295, 2008.
• Réka Albert, Bhaskar DasGupta, Riccardo Dondi and Eduardo Sontag, Inferring (Biological) Signal Transduction Networks via Transitive Reductions of Directed Graphs, Algorithmica, 51 (2), 129-159, 2008.
• Réka Albert, Bhaskar DasGupta, Riccardo Dondi, Eduardo Sontag, Alexander Zelikovsky and Kelly Westbrook, A Novel Method for Signal Transduction Network Inference from Indirect Experimental Evidence, Journal of Computational Biology , 14 (7), 927-949, 2007 (extended abstract in 7^th Workshop on Algorithms in Bioinformatics (WABI), R. Giancarlo and S. Hannenhalli (Eds.), LNBI 4645, Springer-Verlag, 407-419, 2007)

for more details about the network synthesis procedure