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
- R�ka 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, R�ka
Albert and Bhaskar DasGupta,
NET-SYNTHESIS:
A software for synthesis, inference and simplification of signal
transduction networks , Bioinformatics,
24 (2), 293-295, 2008.
- R�ka 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.
- R�ka 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 7th 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