1.1 Release Notes
Since the initial developmental
release of GeNetViz effort has been placed on the ability to visualize large
network graphs while remaining user friendly and useful as a pattern identification
tool for bioinformatics. Many exisitng commercial and open source network graph
tools can handle only small graphs, on the order of a few hundred vertices and
edges at the most. While they have the ability to exceed that limit these tools
become sluggish and cumbersome. Thus, large data sets must be preprocessed,
filtering out data to produce a network graph size that is acceptable to the
tool being used to analyze it. It is the goal of the GeNetViz development team
to provide a tool that can accept larger data sets with reduced application
sluggishness so that a more accurate assesment of the data can be perform by
a general user. Furthermore, there are several disciplines within the bioinformatics
community that can benefit from network graph analysis, but the nature of the
data and the tools used for analysis may differ. GeNetViz has been developed
as a modular environment with key advantages such as,
- Custom modules may be
developed by users and included in GeNetViz as a command line argument. A
novice developer/biologist may include custom bits of functionality interacting
with the application programming interface (api) with out getting into the
GeNetViz source code.
- As GeNetViz grows serving
the needs of biologists in differing fields, the user may enable and disable
modules that are not suitable or useful to their work, customizing their enviroment
for their particular needs.
In addition to the above,
several new features appear in the version 1.1 release:
of vertex annotation, i.e. shape, color, size, transparency, and eccentricity.
- Go Onotology annotation
by gene locus link identification is now performed by obtaining the GoTree
tabular data from a remote location reducing application download time by
- Group definition and
annotation. Subsets of vertices may be defined and annotated to show uniqueness
or importance within a data set.
- A non-visual mode is
provided for analysis of the graph usign statistical analysis tools. This
is often beneficial when the data set is so large that it exceeds memory on
the local pc.
Still in a development phase,
GeNetViz will be molded to provided a more sophisticated management of the multithreaded
environment to keep the user in control of desktop actions and not the application.
Additional tools will be developed which may include,
- Layout of large data
sets, probably in a parallel environment,
- Client-server environment
providing remote tools for network analysis, such as the above,
- Database interaction
for storage of experimental and network graph data supporting work flow,
- Update of the desktop
environment to improve user friendliness and management of multiple graphs.
developed and maintained by Shawn Ericson, Bing Zhang, Stephen Kirov,
and Jay Snoddy
ReleaseNotes_v1.1.htm, Website author: Shawn Ericson, Last revised: October